{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chapter 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:80% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.core.display import display, HTML\n",
    "display(HTML(\"<style>.container { width:80% !important; }</style>\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    import google.colab\n",
    "    import requests\n",
    "    url = 'https://raw.githubusercontent.com/dvgodoy/PyTorchStepByStep/master/config.py'\n",
    "    r = requests.get(url, allow_redirects=True)\n",
    "    open('config.py', 'wb').write(r.content)    \n",
    "except ModuleNotFoundError:\n",
    "    pass\n",
    "\n",
    "from config import *\n",
    "config_chapter4()\n",
    "# This is needed to render the plots in this chapter\n",
    "from plots.chapter4 import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "import numpy as np\n",
    "from PIL import Image\n",
    "\n",
    "import torch\n",
    "import torch.optim as optim\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "\n",
    "from torch.utils.data import DataLoader, Dataset, random_split, WeightedRandomSampler, SubsetRandomSampler\n",
    "from torchvision.transforms import Compose, ToTensor, Normalize, ToPILImage, RandomHorizontalFlip, Resize\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('fivethirtyeight')\n",
    "%matplotlib inline\n",
    "\n",
    "from data_generation.image_classification import generate_dataset\n",
    "from stepbystep.v0 import StepByStep\n",
    "from plots.chapter4 import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Classifying Images"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Generation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "images, labels = generate_dataset(img_size=5, n_images=300, binary=True, seed=13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x540 with 30 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plot_images(images, labels, n_plot=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Images and Channels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_r  = np.zeros((5, 5), dtype=np.uint8)\n",
    "image_r[:, 0] = 255\n",
    "image_r[:, 1] = 128\n",
    "\n",
    "image_g = np.zeros((5, 5), dtype=np.uint8)\n",
    "image_g[:, 1] = 128\n",
    "image_g[:, 2] = 255\n",
    "image_g[:, 3] = 128\n",
    "\n",
    "image_b = np.zeros((5, 5), dtype=np.uint8)\n",
    "image_b[:, 3] = 128\n",
    "image_b[:, 4] = 255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_gray = .2126*image_r + .7152*image_g + .0722*image_b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_rgb = np.stack([image_r, image_g, image_b], axis=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x396 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = image_channels(image_r, image_g, image_b, image_rgb, image_gray, rows=(0, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x396 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = image_channels(image_r, image_g, image_b, image_rgb, image_gray, rows=(0, 2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### NCHW vs NHWC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(300, 1, 5, 5)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "images.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[  0, 255,   0,   0,   0],\n",
       "        [  0,   0, 255,   0,   0],\n",
       "        [  0,   0,   0, 255,   0],\n",
       "        [  0,   0,   0,   0, 255],\n",
       "        [  0,   0,   0,   0,   0]]], dtype=uint8)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "example = images[7]\n",
    "example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5, 5, 1)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "example_hwc = np.transpose(example, (1, 2, 0))\n",
    "example_hwc.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[  0],\n",
       "        [255],\n",
       "        [  0],\n",
       "        [  0],\n",
       "        [  0]],\n",
       "\n",
       "       [[  0],\n",
       "        [  0],\n",
       "        [255],\n",
       "        [  0],\n",
       "        [  0]],\n",
       "\n",
       "       [[  0],\n",
       "        [  0],\n",
       "        [  0],\n",
       "        [255],\n",
       "        [  0]],\n",
       "\n",
       "       [[  0],\n",
       "        [  0],\n",
       "        [  0],\n",
       "        [  0],\n",
       "        [255]],\n",
       "\n",
       "       [[  0],\n",
       "        [  0],\n",
       "        [  0],\n",
       "        [  0],\n",
       "        [  0]]], dtype=uint8)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "example_hwc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Torchvision"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Transforms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([1, 5, 5])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensorizer = ToTensor()\n",
    "example_tensor = tensorizer(example_hwc)\n",
    "example_tensor.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[[0., 1., 0., 0., 0.],\n",
       "         [0., 0., 1., 0., 0.],\n",
       "         [0., 0., 0., 1., 0.],\n",
       "         [0., 0., 0., 0., 1.],\n",
       "         [0., 0., 0., 0., 0.]]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "example_tensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'PIL.Image.Image'>\n"
     ]
    }
   ],
   "source": [
    "example_img = ToPILImage()(example_tensor)\n",
    "print(type(example_img))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQQAAAEJCAYAAAByllnUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAMDklEQVR4nO3dX0jV9x/H8dfJOFFGfCUkmByRyQI9K7JAWYNJSgdCmjKIiq4ktmjCiP6gdmPrYkRRYItFFIKgjMQdhjnKK7c0qQURsboJvEmiI7nOgSOEcI6/i7H37+fP6flqne/3ePZ83PU9Hs8bqWef8/0eP99APB6fFQBIWuX3AAByB0EAYAgCAEMQABiCAMAQBACGIAAwBAGAWZ2tb+w4Tra+ddbMzq7Mz2gFAgG/R8AKEY/HF32cFQIAQxAAGIIAwBAEAIYgADAEAYAhCAAMQQBgCAIAQxAAGIIAwBAEAIYgADAEAYAhCAAMQQBgXAfhxo0b2rp1qzZt2qTa2lqNjY1lcy4APnAVhGg0qra2Np04cUJ3795VdXW19u3bpxcvXmR7PgAeCri5t2N9fb3C4bAuX75sx7Zv367GxkZ1dHT843PYQs07bKEGt955C7WZmRk9fvxYdXV1c47X1dXpwYMH7zYdgJySMQhTU1NKpVIqLi6ec7y4uFiTk5NZGwyA91yfVPz/Zens7CxLVSDPZAzCxo0bVVBQMG818Pr163mrBgArW8YgBINBbdu2TcPDw3OODw8Pq6amJmuDAfCeqxu1tLS06MiRI9qxY4dqamrU1dWlV69eqbm5OdvzAfCQqyB88cUX+vPPP3XhwgXFYjFVVFSor69PpaWl2Z4PgIdcfQ5hOfgcgnc4uQu3uJUbANcIAgBDEAAYggDAEAQAhiAAMAQBgCEIAAxBAGAIAgBDEAAYggDAEAQAhiAAMAQBgCEIAIyrHZP+LVbqRiMrdWMXaeX+zPMVKwQAhiAAMAQBgCEIAAxBAGAIAgBDEAAYggDAEAQAhiAAMAQBgCEIAAxBAGAIAgBDEAAYggDAEAQAhiAAMAQBgHEVhHv37unAgQOqqKiQ4zjq7e3N9lwAfOAqCNPT06qsrNS5c+e0du3abM8EwCeudl2ORCKKRCKSpK+//jqrAwHwD+cQABiCAMAQBACGIAAwBAGAcXWVIZlManx8XJKUTqc1MTGhJ0+eqKioSKFQKKsDAvBOIB6PZ7xT6MjIiPbu3Tvv+MGDB3X16tV/fI7jOO8+HVzhZq9wKx6PL/q4qyAsB0HwDkGAW5mCwDkEAIYgADAEAYAhCAAMQQBgCAIAQxAAGIIAwBAEAIYgADAEAYAhCAAMQQBgCAIAQxAAGIIAwLjaQg25bSVvMsLmLrmFFQIAQxAAGIIAwBAEAIYgADAEAYAhCAAMQQBgCAIAQxAAGIIAwBAEAIYgADAEAYAhCAAMQQBgCAIAQxAAmIxBuHTpknbt2qVQKKTy8nLt379fz54982I2AB7LGITR0VEdPnxYQ0NDGhgY0OrVq9XU1KQ3b954MR8ADwXi8fiSdrlMJpMqLS1Vb2+v9uzZs+DXOY7zzsMh/7HJqrfi8fiijy/5HEIymVQ6neYfPJCHlhyEtrY2bdmyRdXV1dmYB4CPlnRfhtOnT+v+/fu6c+eOCgoKsjUTAJ+4DkJ7e7ui0ahu3bqlsrKyLI4EwC+ugtDa2qpoNKrBwUFt3rw52zMB8EnGIJw8eVI3b95UT0+PHMdRLBaTJBUWFmr9+vVZHxCAdzJedlzoakJra6va29uX/Dzgf3HZ0VuZLjtmXCFk+gYA8ge/ywDAEAQAhiAAMAQBgCEIAAxBAGAIAgBDEAAYggDAEAQAhiAAMAQBgCEIAAxBAGAIAgBDEACYJe26DLxvK3HXob+txN2eEonEoo+zQgBgCAIAQxAAGIIAwBAEAIYgADAEAYAhCAAMQQBgCAIAQxAAGIIAwBAEAIYgADAEAYAhCAAMQQBgCAIAQxAAmIxBuH79unbu3KlQKKRQKKTdu3draGjIi9kAeCwQj8cX3Snyl19+UTAYVHl5udLptH788Ud1dnbq119/1ccff7zg8xzHee/DArkkHzdZzRiEf1JWVqaOjg41Nzcv+DUEAfkuH4OwpG3YU6mUfv75Z01PT6u6uvqdBgOQe1wF4enTp4pEInr79q0KCwvV09OjcDic7dkAeMzVW4aZmRlNTEwokUhoYGBA3d3dGhwcVGVl5YLP4S0D8l0+vmVY1jmExsZGhUIhXblyZcGvIQjId/kYhGV9DiGdTmtmZmZZAwHIXRnPIZw5c0aRSEQlJSVKJpPq7+/X6Oio+vr6vJgPgIcyBiEWi+mrr77S5OSkNmzYoHA4rP7+ftXX13sxHwAPLescghucQ0C+4xwCgLxGEAAYggDAEAQAhiAAMAQBgCEIAAxBAGAIAgBDEAAYggDAEAQAhiAAMAQBgCEIAAxBAGCWdF8GAP8VCAT8HmHJ4vH4oo+zQgBgCAIAQxAAGIIAwBAEAIYgADAEAYAhCAAMQQBgCAIAQxAAGIIAwBAEAIYgADAEAYAhCAAMQQBgCAIAQxAAmCUH4eLFi3IcR6dOncrGPAB8tKQgPHz4UN3d3QqHw9maB4CPXAchkUjoyy+/1Pfffy/HcbI5EwCfuA7CsWPH1NjYqNra2mzOA8BHru7L0N3drfHxcV27di3b8wDwUcYgPH/+XGfPntXt27cVDAa9mAmATwLxeHx2sS/o7e1VS0uLCgoK7FgqlVIgENCqVav08uVLrVmzZt7zOM8A5J5Md27KuEJoaGhQVVXVnGMtLS0qLy/X8ePHWTUAeSRjEBzHmfe//bp161RUVKTKysqsDQbAe3xSEYDJeA5huTiHAOQe7v4MwDWCAMAQBACGIAAwBAGAIQgADEEAYAgCAEMQABiCAMAQBACGIAAwBAGAIQgADEEAYFzturwcmX7vGkDuYYUAwBAEAIYgADAEAYAhCADMigjCjRs3tHXrVm3atEm1tbUaGxvzeyRX7t27pwMHDqiiokKO46i3t9fvkVy5dOmSdu3apVAopPLycu3fv1/Pnj3ze6yMrl+/rp07dyoUCikUCmn37t0aGhrye6xluXjxohzH0alTpzx93ZwPQjQaVVtbm06cOKG7d++qurpa+/bt04sXL/weLaPp6WlVVlbq3LlzWrt2rd/juDY6OqrDhw9raGhIAwMDWr16tZqamvTmzRu/R1vUBx98oG+//Va//fabhoeH9dlnn+nQoUP6448//B5tSR4+fKju7m6Fw2HPXztr92V4X+rr6xUOh3X58mU7tn37djU2Nqqjo8PHyZampKRE58+f16FDh/weZcmSyaRKS0vV29urPXv2+D3OkpSVlamjo0PNzc1+j+JKIpFQbW2tOjs7df78eVVWVurChQuevX5OrxBmZmb0+PFj1dXVzTleV1enBw8e+DTVv08ymVQ6nV5RN99JpVL66aefND09rerqar/Hce3YsWNqbGxUbW2tL6+ftU8qvg9TU1NKpVIqLi6ec7y4uFiTk5M+TfXv09bWpi1btqyIf1hPnz5VJBLR27dvVVhYqJ6eHl+W3svR3d2t8fFxXbt2zbcZcjoIfwsEAnP+PDs7O+8YsuP06dO6f/++7ty5o4KCAr/Hyeijjz7SyMiIEomEBgYGdPToUQ0ODub8jYmfP3+us2fP6vbt277eUT2ng7Bx40YVFBTMWw28fv163qoB7197e7ui0ahu3bqlsrIyv8dxJRgM6sMPP5QkVVVV6dGjR/rhhx905coVnydb3O+//66pqSl98skndiyVSmlsbExdXV16+fKl1qxZk/U5cjoIwWBQ27Zt0/DwsJqamuz48PCwPv/8cx8ny3+tra2KRqMaHBzU5s2b/R5n2dLptGZmZvweI6OGhgZVVVXNOdbS0qLy8nIdP37cs1VDTgdB+uuHcuTIEe3YsUM1NTXq6urSq1evVsRZ42QyqfHxcUl//cWcmJjQkydPVFRUpFAo5PN0Czt58qRu3rypnp4eOY6jWCwmSSosLNT69et9nm5hZ86cUSQSUUlJiZLJpPr7+zU6Oqq+vj6/R8vIcZx5J23XrVunoqIiT9/u5PxlR+mvDyZ1dnYqFoupoqJC3333nT799FO/x8poZGREe/funXf84MGDunr1qg8TubPQ1YTW1la1t7d7PI17R48e1cjIiCYnJ7VhwwaFw2F98803qq+v93u0ZWloaPD8suOKCAIAb+T05xAAeIsgADAEAYAhCAAMQQBgCAIAQxAAGIIAwBAEAOY/5rMJfm2UBHMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(example_img, cmap='gray')\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Transforms on Images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "flipper = RandomHorizontalFlip(p=1.0)\n",
    "flipped_img = flipper(example_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(flipped_img, cmap='gray')\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Transforms on Tensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[[0., 0., 0., 1., 0.],\n",
       "         [0., 0., 1., 0., 0.],\n",
       "         [0., 1., 0., 0., 0.],\n",
       "         [1., 0., 0., 0., 0.],\n",
       "         [0., 0., 0., 0., 0.]]])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_tensor = tensorizer(flipped_img)\n",
    "img_tensor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Normalize Transform"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\Large\n",
    "\\begin{aligned}\n",
    "\\text{input} = 0 \\implies \\frac{0 - \\text{mean}}{\\text{std}}= \\frac{0 - 0.5}{0.5}&=-1\n",
    "\\\\\n",
    "\\text{input} = 1 \\implies \\frac{1 - \\text{mean}}{\\text{std}}= \\frac{1 - 0.5}{0.5}&=1\n",
    "\\end{aligned}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[[-1., -1., -1.,  1., -1.],\n",
       "         [-1., -1.,  1., -1., -1.],\n",
       "         [-1.,  1., -1., -1., -1.],\n",
       "         [ 1., -1., -1., -1., -1.],\n",
       "         [-1., -1., -1., -1., -1.]]])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "normalizer = Normalize(mean=(.5,), std=(.5,))\n",
    "normalized_tensor = normalizer(img_tensor)\n",
    "normalized_tensor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Composing Transforms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "composer = Compose([RandomHorizontalFlip(p=1.0),\n",
    "                    Normalize(mean=(.5,), std=(.5,))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor(True)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "composed_tensor = composer(example_tensor)\n",
    "(composed_tensor == normalized_tensor).all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[  0 255   0   0   0]\n",
      "  [  0   0 255   0   0]\n",
      "  [  0   0   0 255   0]\n",
      "  [  0   0   0   0 255]\n",
      "  [  0   0   0   0   0]]]\n",
      "tensor([[[0., 1., 0., 0., 0.],\n",
      "         [0., 0., 1., 0., 0.],\n",
      "         [0., 0., 0., 1., 0.],\n",
      "         [0., 0., 0., 0., 1.],\n",
      "         [0., 0., 0., 0., 0.]]])\n"
     ]
    }
   ],
   "source": [
    "print(example)\n",
    "print(example_tensor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "example_tensor = torch.as_tensor(example / 255).float()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Builds tensors from numpy arrays BEFORE split\n",
    "x_tensor = torch.as_tensor(images / 255).float()\n",
    "y_tensor = torch.as_tensor(labels.reshape(-1, 1)).float()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dataset Transforms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TransformedTensorDataset(Dataset):\n",
    "    def __init__(self, x, y, transform=None):\n",
    "        self.x = x\n",
    "        self.y = y\n",
    "        self.transform = transform\n",
    "        \n",
    "    def __getitem__(self, index):\n",
    "        x = self.x[index]\n",
    "        \n",
    "        if self.transform:\n",
    "            x = self.transform(x)\n",
    "        \n",
    "        return x, self.y[index]\n",
    "        \n",
    "    def __len__(self):\n",
    "        return len(self.x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "composer = Compose([RandomHorizontalFlip(p=0.5),\n",
    "                    Normalize(mean=(.5,), std=(.5,))])\n",
    "\n",
    "dataset = TransformedTensorDataset(x_tensor, y_tensor, transform=composer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SubsetRandomSampler"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Helper Function #4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "def index_splitter(n, splits, seed=13):\n",
    "    idx = torch.arange(n)\n",
    "    # Makes the split argument a tensor\n",
    "    splits_tensor = torch.as_tensor(splits)\n",
    "    # Finds the correct multiplier, so we don't have\n",
    "    # to worry about summing up to N (or one)\n",
    "    multiplier = n / splits_tensor.sum()    \n",
    "    splits_tensor = (multiplier * splits_tensor).long()\n",
    "    # If there is a difference, throws at the first split\n",
    "    # so random_split does not complain\n",
    "    diff = n - splits_tensor.sum()\n",
    "    splits_tensor[0] += diff\n",
    "    # Uses PyTorch random_split to split the indices\n",
    "    torch.manual_seed(seed)\n",
    "    return random_split(idx, splits_tensor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<torch.utils.data.dataset.Subset at 0x7efe651082d0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_idx, val_idx = index_splitter(len(x_tensor), [80, 20])\n",
    "train_idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " 164,\n",
       " 222,\n",
       " 10,\n",
       " 161]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_idx.indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_sampler = SubsetRandomSampler(train_idx)\n",
    "val_sampler = SubsetRandomSampler(val_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Builds a loader of each set\n",
    "train_loader = DataLoader(dataset=dataset, batch_size=16, sampler=train_sampler)\n",
    "val_loader = DataLoader(dataset=dataset, batch_size=16, sampler=val_sampler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(15, 4)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(iter(train_loader)), len(iter(val_loader))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Augmentation Transformations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train_tensor = x_tensor[train_idx]\n",
    "y_train_tensor = y_tensor[train_idx]\n",
    "\n",
    "x_val_tensor = x_tensor[val_idx]\n",
    "y_val_tensor = y_tensor[val_idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_composer = Compose([RandomHorizontalFlip(p=.5),\n",
    "                          Normalize(mean=(.5,), std=(.5,))])\n",
    "\n",
    "val_composer = Compose([Normalize(mean=(.5,), std=(.5,))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dataset = TransformedTensorDataset(x_train_tensor, y_train_tensor, transform=train_composer)\n",
    "val_dataset = TransformedTensorDataset(x_val_tensor, y_val_tensor, transform=val_composer)\n",
    "\n",
    "# Builds a loader of each set\n",
    "train_loader = DataLoader(dataset=train_dataset, batch_size=16, shuffle=True)\n",
    "val_loader = DataLoader(dataset=val_dataset, batch_size=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### WeightedRandomSampler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0., 1.]) tensor([ 80, 160])\n"
     ]
    }
   ],
   "source": [
    "classes, counts = y_train_tensor.unique(return_counts=True)\n",
    "print(classes, counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0.0125, 0.0063])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights = 1.0 / counts.float()\n",
    "weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([240])\n",
      "tensor([0.0063, 0.0063, 0.0063, 0.0063, 0.0063, 0.0125, 0.0063, 0.0063, 0.0063,\n",
      "        0.0063])\n",
      "tensor([1., 1., 1., 1., 1., 0., 1., 1., 1., 1.])\n"
     ]
    }
   ],
   "source": [
    "sample_weights = weights[y_train_tensor.squeeze().long()]\n",
    "\n",
    "print(sample_weights.shape)\n",
    "print(sample_weights[:10])\n",
    "print(y_train_tensor[:10].squeeze())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "generator = torch.Generator()\n",
    "\n",
    "sampler = WeightedRandomSampler(\n",
    "    weights=sample_weights,\n",
    "    num_samples=len(sample_weights),\n",
    "    generator=generator,\n",
    "    replacement=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_loader = DataLoader(dataset=train_dataset, batch_size=16, sampler=sampler)\n",
    "val_loader = DataLoader(dataset=val_dataset, batch_size=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Helper Function #5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_balanced_sampler(y):\n",
    "    # Computes weights for compensating imbalanced classes\n",
    "    classes, counts = y.unique(return_counts=True)\n",
    "    weights = 1.0 / counts.float()\n",
    "    sample_weights = weights[y.squeeze().long()]\n",
    "    # Builds sampler with compute weights\n",
    "    generator = torch.Generator()\n",
    "    sampler = WeightedRandomSampler(\n",
    "        weights=sample_weights,\n",
    "        num_samples=len(sample_weights),\n",
    "        generator=generator,\n",
    "        replacement=True\n",
    "    )\n",
    "    return sampler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "sampler = make_balanced_sampler(y_train_tensor)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Seeds and more (seeds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_loader.sampler.generator.manual_seed(42)\n",
    "random.seed(42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor(123.)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.tensor([t[1].sum() for t in iter(train_loader)]).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "def set_seed(self, seed=42):\n",
    "    torch.backends.cudnn.deterministic = True\n",
    "    torch.backends.cudnn.benchmark = False    \n",
    "    torch.manual_seed(seed)\n",
    "    np.random.seed(seed)\n",
    "    random.seed(seed)\n",
    "    try:\n",
    "        self.train_loader.sampler.generator.manual_seed(seed)\n",
    "    except AttributeError:\n",
    "        pass\n",
    "    \n",
    "setattr(StepByStep, 'set_seed', set_seed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Putting It Together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Builds tensors from numpy arrays BEFORE split\n",
    "# Modifies the scale of pixel values from [0, 255] to [0, 1]\n",
    "x_tensor = torch.as_tensor(images / 255).float()\n",
    "y_tensor = torch.as_tensor(labels.reshape(-1, 1)).float()\n",
    "\n",
    "# Uses index_splitter to generate indices for training and\n",
    "# validation sets\n",
    "train_idx, val_idx = index_splitter(len(x_tensor), [80, 20])\n",
    "\n",
    "# Uses indices to perform the split\n",
    "x_train_tensor = x_tensor[train_idx]\n",
    "y_train_tensor = y_tensor[train_idx]\n",
    "x_val_tensor = x_tensor[val_idx]\n",
    "y_val_tensor = y_tensor[val_idx]\n",
    "\n",
    "# Builds different composers because of data augmentation on training set\n",
    "train_composer = Compose([RandomHorizontalFlip(p=.5),\n",
    "                          Normalize(mean=(.5,), std=(.5,))])\n",
    "val_composer = Compose([Normalize(mean=(.5,), std=(.5,))])\n",
    "# Uses custom dataset to apply composed transforms to each set\n",
    "train_dataset = TransformedTensorDataset(x_train_tensor, y_train_tensor, transform=train_composer)\n",
    "val_dataset = TransformedTensorDataset(x_val_tensor, y_val_tensor, transform=val_composer)\n",
    "\n",
    "# Builds a weighted random sampler to handle imbalanced classes\n",
    "sampler = make_balanced_sampler(y_train_tensor)\n",
    "\n",
    "# Uses sampler in the training set to get a balanced data loader\n",
    "train_loader = DataLoader(dataset=train_dataset, batch_size=16, sampler=sampler)\n",
    "val_loader = DataLoader(dataset=val_dataset, batch_size=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pixels as Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([16, 1, 5, 5])"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummy_xs, dummy_ys = next(iter(train_loader))\n",
    "dummy_xs.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([16, 25])\n",
      "tensor([-1., -1., -1.,  1., -1., -1., -1., -1.,  1., -1., -1., -1., -1.,  1.,\n",
      "        -1., -1., -1., -1.,  1., -1., -1., -1., -1.,  1., -1.])\n"
     ]
    }
   ],
   "source": [
    "flattener = nn.Flatten()\n",
    "dummy_xs_flat = flattener(dummy_xs)\n",
    "\n",
    "print(dummy_xs_flat.shape)\n",
    "print(dummy_xs_flat[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Shallow Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\Large \\text{P}(y=1) = \\sigma(z) = \\sigma(w_0x_0+w_1x_1+\\cdots+w_{24}x_{24})\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](images/classification.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Notation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\Large W =\n",
    "\\underset{(25 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "w_0 \\\\\n",
    "w_1 \\\\\n",
    "\\vdots \\\\\n",
    "w_{24}\n",
    "\\end{bmatrix}};\n",
    "X = \n",
    "\\underset{(25 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "x_0 \\\\\n",
    "x_1 \\\\\n",
    "\\vdots \\\\\n",
    "x_{24}\n",
    "\\end{bmatrix}}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\Large \n",
    "\\begin{aligned}\n",
    "z\n",
    "& = W^T \\cdot X \n",
    "=\\underset{(1 \\times 25)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T} & -\\\\\n",
    "\\end{bmatrix}}\n",
    "\\underset{(25 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "x_0 \\\\\n",
    "x_1 \\\\\n",
    "\\vdots \\\\\n",
    "x_{24}\n",
    "\\end{bmatrix}} \n",
    "=\n",
    "\\underset{(1 \\times 25)}{\n",
    "\\begin{bmatrix}\n",
    "w_0 & w_1 & \\cdots & w_{24}\n",
    "\\end{bmatrix}}\n",
    "\\underset{(25 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "x_0 \\\\\n",
    "x_1 \\\\\n",
    "\\vdots \\\\\n",
    "x_{24}\n",
    "\\end{bmatrix}}\n",
    "\\\\\n",
    "& = w_0x_0 + w_1x_1 + \\cdots + w_{24}x_{24}\n",
    "\\end{aligned}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sets learning rate - this is \"eta\" ~ the \"n\" like Greek letter\n",
    "lr = 0.1\n",
    "\n",
    "torch.manual_seed(17)\n",
    "# Now we can create a model\n",
    "model_logistic = nn.Sequential()\n",
    "model_logistic.add_module('flatten', nn.Flatten())\n",
    "model_logistic.add_module('output', nn.Linear(25, 1, bias=False))\n",
    "model_logistic.add_module('sigmoid', nn.Sigmoid())\n",
    "\n",
    "# Defines a SGD optimizer to update the parameters \n",
    "optimizer_logistic = optim.SGD(model_logistic.parameters(), lr=lr)\n",
    "\n",
    "# Defines a binary cross entropy loss function\n",
    "binary_loss_fn = nn.BCELoss()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_epochs = 100\n",
    "\n",
    "sbs_logistic = StepByStep(model_logistic, binary_loss_fn, optimizer_logistic)\n",
    "sbs_logistic.set_loaders(train_loader, val_loader)\n",
    "sbs_logistic.train(n_epochs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sbs_logistic.plot_losses()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Deep-ish Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](images/classification_equiv.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sets learning rate - this is \"eta\" ~ the \"n\" like Greek letter\n",
    "lr = 0.1\n",
    "\n",
    "torch.manual_seed(17)\n",
    "# Now we can create a model\n",
    "model_nn = nn.Sequential()\n",
    "model_nn.add_module('flatten', nn.Flatten())\n",
    "model_nn.add_module('hidden0', nn.Linear(25, 5, bias=False))\n",
    "model_nn.add_module('hidden1', nn.Linear(5, 3, bias=False))\n",
    "model_nn.add_module('output', nn.Linear(3, 1, bias=False))\n",
    "model_nn.add_module('sigmoid', nn.Sigmoid())\n",
    "\n",
    "# Defines a SGD optimizer to update the parameters \n",
    "optimizer_nn = optim.SGD(model_nn.parameters(), lr=lr)\n",
    "\n",
    "# Defines a binary cross entropy loss function\n",
    "binary_loss_fn = nn.BCELoss()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_epochs = 100\n",
    "\n",
    "sbs_nn = StepByStep(model_nn, binary_loss_fn, optimizer_nn)\n",
    "sbs_nn.set_loaders(train_loader, val_loader)\n",
    "sbs_nn.train(n_epochs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sbs_nn.plot_losses()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = figure5(sbs_logistic, sbs_nn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show Me the Math!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\large\n",
    "\\begin{array}{rcccccccccccc}\n",
    "\\text{Hidden}\\ \\#0 & & & & & & & &\n",
    "\\underset{(5 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "z_{00} \\\\\n",
    "z_{01} \\\\\n",
    "z_{02} \\\\\n",
    "z_{03} \\\\\n",
    "z_{04} \\\\\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "=\n",
    "&\n",
    "\\underset{(5 \\times 25)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{00} & -\\\\\n",
    "- & w^{T}_{01} & -\\\\\n",
    "- & w^{T}_{02} & -\\\\\n",
    "- & w^{T}_{03} & -\\\\\n",
    "- & w^{T}_{04} & -\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "&\n",
    "\\underset{(25 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "x_0 \\\\\n",
    "\\vdots \\\\\n",
    "x_{11} \\\\\n",
    "\\vdots \\\\\n",
    "x_{24}\n",
    "\\end{bmatrix}}\n",
    "\\\\\n",
    "\\text{Hidden}\\ \\#1 & & & &\n",
    "\\underset{(3 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "z_{10} \\\\\n",
    "z_{11} \\\\\n",
    "z_{12} \\\\\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "=\n",
    "&\n",
    "\\underset{(3 \\times 5)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{10} & -\\\\\n",
    "- & w^{T}_{11} & -\\\\\n",
    "- & w^{T}_{12} & -\\\\\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "&\n",
    "\\underset{(5 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "z_{00} \\\\\n",
    "z_{01} \\\\\n",
    "z_{02} \\\\\n",
    "z_{03} \\\\\n",
    "z_{04} \\\\\n",
    "\\end{bmatrix}}\n",
    "\\\\\n",
    "\\text{Output} &\n",
    "\\underset{(1 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "z_{2}\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "=\n",
    "&\n",
    "\\underset{(1 \\times 3)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{20} & -\\\\\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "\\underset{(3 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "z_{10} \\\\\n",
    "z_{11} \\\\\n",
    "z_{12} \\\\\n",
    "\\end{bmatrix}}\n",
    "\\\\\n",
    "\\hline\n",
    "\\text{substituting } z's... &\n",
    "\\underset{(1 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "z_{2}\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "=\n",
    "&\n",
    "\\underbrace{\n",
    "\\underset{(1 \\times 3)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{20} & -\\\\\n",
    "\\end{bmatrix}}}_{\\text{Output Layer}}\n",
    "&\n",
    "& &\n",
    "\\underbrace{\n",
    "\\underset{(3 \\times 5)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{10} & -\\\\\n",
    "- & w^{T}_{11} & -\\\\\n",
    "- & w^{T}_{12} & -\\\\\n",
    "\\end{bmatrix}}}_{\\text{Hidden Layer #1}}\n",
    "& &\n",
    "& &\n",
    "\\underbrace{\n",
    "\\underset{(5 \\times 25)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{00} & -\\\\\n",
    "- & w^{T}_{01} & -\\\\\n",
    "- & w^{T}_{02} & -\\\\\n",
    "- & w^{T}_{03} & -\\\\\n",
    "- & w^{T}_{04} & -\n",
    "\\end{bmatrix}}}_{\\text{Hidden Layer #0}}\n",
    "&\n",
    "&\n",
    "\\underset{(25 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "x_0 \\\\\n",
    "\\vdots \\\\\n",
    "x_{11} \\\\\n",
    "\\vdots \\\\\n",
    "x_{24}\n",
    "\\end{bmatrix}}\n",
    "\\\\\n",
    "\\text{multiplying...} & &\n",
    "=\n",
    "&\n",
    "\\underbrace{\n",
    "\\underset{(1 \\times 25)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T} & -\\\\\n",
    "\\end{bmatrix}}}_{\\text{Matrices Multiplied}}\n",
    "&\n",
    "& & & & & & & &\n",
    "\\underset{(25 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "x_0 \\\\\n",
    "\\vdots \\\\\n",
    "x_{11} \\\\\n",
    "\\vdots \\\\\n",
    "x_{24}\n",
    "\\end{bmatrix}}\n",
    "\\end{array}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show Me the Code!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([5, 25]), torch.Size([3, 5]), torch.Size([1, 3]))"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_nn_hidden0 = model_nn.hidden0.weight.detach()\n",
    "w_nn_hidden1 = model_nn.hidden1.weight.detach()\n",
    "w_nn_output = model_nn.output.weight.detach()\n",
    "\n",
    "w_nn_hidden0.shape, w_nn_hidden1.shape, w_nn_output.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([1, 25])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_nn_equiv = w_nn_output @ w_nn_hidden1 @ w_nn_hidden0\n",
    "w_nn_equiv.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "w_nn_equiv = w_nn_output.mm(w_nn_hidden1.mm(w_nn_hidden0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([1, 25])"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_logistic_output = model_logistic.output.weight.detach()\n",
    "\n",
    "w_logistic_output.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = weights_comparison(w_logistic_output, w_nn_equiv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "def count_parameters(self):\n",
    "    return sum(p.numel() for p in self.model.parameters() if p.requires_grad)\n",
    "\n",
    "setattr(StepByStep, 'count_parameters', count_parameters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25, 143)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sbs_logistic.count_parameters(), sbs_nn.count_parameters()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Weights as Pixels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([5, 25])"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_nn_hidden0.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = figure7(w_nn_hidden0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Activation Functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sigmoid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\Large \\sigma(z) = \\frac{1}{1 + e^{-z}}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/dvgodoy/projects/PyTorchStepByStep/plots/chapter4.py:175: UserWarning: Matplotlib is currently using module://ipykernel.pylab.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plot_activation(torch.sigmoid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0.0474, 0.5000, 0.9526])"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummy_z = torch.tensor([-3., 0., 3.])\n",
    "torch.sigmoid(dummy_z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0.0474, 0.5000, 0.9526])"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nn.Sigmoid()(dummy_z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hyperbolic Tangent (Tanh)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\Large \\sigma(z) = \\frac{e^z - e^{-z}}{e^z + e^{-z}}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plot_activation(torch.tanh)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([-0.9951,  0.0000,  0.9951])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummy_z = torch.tensor([-3., 0., 3.])\n",
    "torch.tanh(dummy_z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([-0.9951,  0.0000,  0.9951])"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nn.Tanh()(dummy_z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Rectified Linear Unit (ReLU)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\Large\n",
    "\\begin{aligned}\n",
    "\\sigma(z) &=\n",
    "\\begin{cases}\n",
    "z,\\ \\text{if } z \\ge 0\n",
    "\\\\\n",
    "0,\\ \\text{if } z < 0\n",
    "\\end{cases}\n",
    "\\\\\n",
    "& \\text{or}\n",
    "\\\\\n",
    "\\sigma(z) &= \\text{max}(0, z)\n",
    "\\end{aligned}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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YmBg0adJEYDL94RYYGRg/fjxMTEyQlJSEzz77DI0bN4arqyu6d++OrVu3onfv3gAApVKJ6Oho9OnTB7Vq1cKcOXNQWFiIcePGoVmzZqhZsyZatGiBpUuXQq1Wa5+/sLAQ06dPR926dVG3bl1MnjxZssARUHQXkkajwdKlS+Hu7o6aNWuibdu2iI+P195+48YNKJVK7Nq1Cz179oSDgwNat26NpKQk7e2ffvopgL+XrlYqlUX+p0BERCX34MED+Pj44NGjR5L5smXL4OnpKSiV/hn9FpgqSmXx76uD18tITy/R/R89eoSDBw8iNDT0lfsrnz+CfOHChQgNDcW8efMAAGq1GjVr1sTGjRtRtWpV/PLLLxgzZgxsbW3Rr18/AMCKFSuwefNmLF26FG5uboiOjkZCQgKaNWv2ylzz5s3Drl27sHjxYrzzzjs4ffo0xowZA6VSic6dO0vuN2fOHERERCA8PByDBg3C2bNnUadOHWzevBn9+vXDyZMnYWtraxTX3iAiEunp06cICAjA9evXJfMpU6YgICBATChBjL7AyN2VK1eg0WjwzjvvSOaurq7IyMgAAPj6+iIyMhIA8K9//UtbTJ6ZNGmSthzUrVsXv/76K7Zv36693+rVqzF69Gj861//AvB3Cfr+++9fmSk7OxsrV67Ejh070LZtWwCAs7Mzfv75Z6xdu1ZSYIYPH46uXbsCAEJDQ7Ft2zacPXsWbdq0ga2tLQDA3t4eVatWLd0bREREAP7+D+vQoUNx+vRpyTwwMBBffvmloFTisMDI1DfffAO1Wo0xY8YgJydHO2/evHmR+27atAlxcXG4efMmcnJykJ+fD0dHRwBARkYG/vrrL7z//vva+5uYmKBly5ZFVmt85tKlS8jJyUHv3r0lW3/y8/Ph5OQkua+bm5v2YwcHBwDA/fv3S/EVExHR68yYMQN79uyRzDw9PfH1118b7Vovr8MCI1j9+vWhUCiQkpIimTs7OwMAKlasKJm/uJtpx44dCA0Nxdy5c9GqVSvY2NggOjoae/fuLXWmZ8fPxMXFaYvQM2Zm0m8Zc3Nz7cfP/gFpNJpSvzYRERW1Zs0arFy5UjJr0qQJNm3apLOTOQyN0ReYkhyTkpOTo/fjNOzs7NChQwdER0dj6NChqFSpUokef+LECTRv3hxDhw7Vzq5du6b9uEqVKqhZsyZ++ukn7cFdGo0Gv/zyyytPs2vUqBEsLS1x8+bNtzog7Nk/qhcPGCYiouL79ttvMXnyZMmsRo0aUKlUUJbgOE9jw7OQZCAiIgJqtRr//Oc/kZiYiIsXL+Ly5ctITEzEuXPnXruS4jvvvIOzZ8/iwIEDuHLlChYtWoTjx49L7vP5559j6dKl2LVrF1JSUjB58mSkpqa+8jkrV66MUaNGYcaMGYiJicHVq1fx22+/Yf369UVWe3wdR0dHKBQK7N+/Hw8ePNDLejZERMbkzJkzCA4OlpxZam1tjfj4+CJbyMsbo98CYwicnZ3xww8/YMmSJZg/fz5u374Nc3NzNGzYEMHBwRgyZMgrHztw4EAkJydj8ODB0Gg06N69O0aMGIEtW7Zo7zNy5EikpqZi1KhRAAA/Pz/4+Pjg0qVLr3zeadOmwd7eHitWrMD48eNRuXJlNG3aFGPGjCn211WrVi1MmTIF8+bNw+jRo+Hv74/Vq1cX+/FEROXZjRs34OfnhydPnmhnJiYmWL9+Pdzd3QUmkwdFenq60RywkJGR8VYLsonYhaQL5SX32/796lJKSgpcXFxExygx5tY/Q83O3Pr1Yu709HR07ty5yH80IyIiEBwcrO94ryXqPecuJCIiIhnJy8tD3759i5SX0aNHy668iMQCQ0REJBMajQajRo3CkSNHJPOePXsWuWhjeccCQ0REJBNhYWGSy7YAQOvWrbF69WqYmPBX9vP4bhAREclAbGwsFi1aJJnVr18fW7duhZWVlaBU8iW7AhMREQGlUomJEyeKjkJERKQXp06dKnKWp52dHRISEngplleQVYE5ffo0Nm3aJFmevqS4Cqxx4t8rERmrCxcuYNKkSSgoKNDOLC0tERcXhwYNGghMJm+yKTAZGRkYMmQIli9fXuqVBStUqCA5X56Mx5MnTwzyVHEiote5e/cufH19kZ2dLZlHRUWhdevWglIZBtksZDd27Fj06NEDnp6eRfYBFpelpSUKCgq0V3EuqcePH8PGxqZUjxWpPOQ2MzODpaVlGSciItKfrKws+Pn54datW5L5nDlz0LNnT0GpDIcsCsymTZtw9epVREVFFfsxL178UFeev/KzIWFu/Sur78Gyxtz6Z6jZmbvsFBQUYMKECfjtt98k888++wxdunQxiK/heWWV93UL5AkvMCkpKZgzZw6+/fbbEl1RsyxW/TOWFRwNhaHmBgw3O3Prn6FmZ+6yo9FoMH78eBw7dkwy79y5M6KiomBmJvxXc4mIes+Fv0s//vgj0tLS0KZNG+2ssLAQx48fx/r163Hnzh3uOiAiIqOxfPlyrF+/XjJr1KgR1q1bZ3DlRSTh75S3tzeaN28umY0YMQINGjTAF198UaKtMkRERHK2c+dOhIaGSmZ16tRBZGQkKlWqJCiVYRJeYJRKZZGzjipWrAhbW1u4uroKSkVERKRbJ0+eREhIiGRmY2MDlUoFc3NzQakMl2xOoyYiIjJWV65cQWBgIHJzc7UzMzMzxMTE8D/rpSR8C8zL7Nu3T3QEIiIinUhLS4OPjw8ePnwomS9duhSenp6CUhk+boEhIiIqI0+fPkVAQACuXr0qmX/55ZcICgoSlMo4sMAQERGVAbVajWHDhuHHH3+UzP39/TFlyhRBqYwHCwwREVEZmDVrFnbu3CmZffjhh1i2bBkUCoWgVMaDBYaIiEjH1q1bh2XLlklmjRs3RkxMDJcH0REWGCIiIh3av38/Jk6cKJnVqFEDKpWq1BcrpqJYYIiIiHQkOTkZgwYNglqt1s4qVqyIbdu2wcnJSWAy48MCQ0REpAM3b96En58fsrOztTMTExOsW7euyIrz9PZYYIiIiN5Seno6fH19kZqaKpkvXLgQXbt2FZTKuLHAEBERvYW8vDz069cPv//+u2Q+cuRIDBkyRFAq48cCQ0REVEoajQZjxozBDz/8IJl3794dc+bMEZSqfGCBISIiKqVFixYhLi5OMnv//fcRFRUFExP+ii1LfHeJiIhKIS4uDmFhYZJZvXr1EBcXBysrK0Gpyg8WGCIiohI6fPgwRo0aJZnZ2toiISEB1apVE5SqfGGBISIiKoHff/8dffv2RUFBgXZmaWmJrVu34p133hGYrHxhgSEiIiqm1NRU+Pj44PHjx5L56tWr0aZNG0GpyicWGCIiomLIysqCn58fbt26JZnPmjULvXr1EpSq/GKBISIieoPCwkIEBwcjOTlZMh84cCDGjBkjKFX5xgJDRET0GhqNBpMnT8b+/fsl806dOiE8PBwKhUJQsvKNBYaIiOg1Vq5ciejoaMmsadOmWL9+PczMzASlIhYYIiKiV9i1axdmzJghmdWuXRsqlQqVK1cWlIoAFhgiIqKX+vHHHxESEgKNRqOdVa5cGSqVCg4ODgKTEcACQ0REVMTVq1cREBCAnJwc7czMzAybN2+Gm5ubwGT0DAsMERHRcx4+fAgfHx+kpaVJ5pGRkWjfvr2gVPQiFhgiIqL/LycnB4GBgbhy5YpkPmHCBPTt21dQKnoZFhgiIiIAarUaw4cPx8mTJyVzX19fTJs2TVAqehUWGCIiIgBz5szBjh07JLN27dph+fLlXOtFhlhgiIio3NuwYQO+/vpryaxhw4bYsmULLC0tBaWi12GBISKicu3AgQOYMGGCZGZvbw+VSgWlUikoFb0JCwwREZVbv/76KwYMGIDCwkLtzMrKCvHx8XB2dhYXjN6IBYaIiMqlW7duwd/fH9nZ2dqZQqHA2rVr0aJFC4HJqDhYYIiIqNzJyMiAr68v7t69K5kvWLAA3t7eglJRSbDAEBFRuZKfn48BAwbgwoULkvmwYcMQEhIiKBWVFAsMERGVGxqNBuPGjUNSUpJk3q1bN8ybN09QKioNFhgiIio3Fi9ejC1btkhmHh4eWLNmDUxNTQWlotJggSEionIhPj4e8+fPl8zq1q2LuLg4VKxYUVAqKi0WGCIiMnpHjhzByJEjJTOlUonExETY29sLSkVvgwWGiIiM2qVLl9CnTx/k5+drZxYWFoiNjYWLi4vAZPQ2WGCIiMho3bt3Dz4+PsjIyJDMV61ahX/84x+CUpEusMAQEZFRys7Ohp+fH/7880/JPDQ0FL179xaUinSFBYaIiIxOYWEhBg8ejDNnzkjm/fr1w7hx4wSlIl1igSEiIqMzdepUfPvtt5JZx44dERERAYVCISgV6RILDBERGZVVq1YhKipKMnNzc8OGDRtgbm4uKBXpmvACEx0djbZt28LR0RGOjo7o1KkT9u/fLzoWEREZoKSkJEybNk0yq1WrFlQqFWxsbASlorIgvMDUqlULs2fPxuHDh5GUlISPPvoIQUFBOHfunOhoRERkQH766SfMmDEDGo1GO6tcuTLi4+NRu3ZtgcmoLJiJDvDiVT9nzJiBdevW4fTp03j33XcFpSIiIkNy/fp1+Pv7Izc3VzszNTXFxo0b0bRpU4HJqKwILzDPKywsxM6dO5GdnY1WrVqJjkNERAbg0aNH8PHxwYMHDyTzyMhIdOzYUVAqKmuK9PR0zZvvVrbOnz8PLy8v5OTkwNraGtHR0ejcufNrH5OSkqKndEREJFd5eXkYOXJkkdOlBw4ciOHDhwtKRbryupWSZVFg8vLycOvWLWRkZGD37t3YtGkT9u7dC1dXV73mSElJMchlpZlb/ww1O3Prn6FmN4TcarUaQ4cORWJiomTeu3dvrFmzBiYmwg/zLDZDeL9fRVR2WexCsrCwQP369QEAzZs3xy+//IJVq1ZhxYoVgpMREZFczZ8/v0h5ad68OVauXGlQ5YVKR5Z/w2q1Gnl5eaJjEBGRTG3atAkRERGSmYuLC8LDw2FpaSkoFemT8C0ws2bNgpeXF2rXro2srCwkJibi6NGjUKlUoqMREZEMHTx4EF988YVkVq1aNSQkJEiuOE3GTXiBSU1NxdChQ3Hv3j3Y2NjAzc0NiYmJPHKciIiKOHv2LPr374/CwkLtzMrKCtu2bYOzszNP8ChHhBeY1atXi45AREQG4Pbt2/Dz80NWVpZ2plAosGbNGnh4eAhMRiLI8hgYIiKi5z1+/Bi+vr64c+eOZD5//nx8+umnglKRSCwwREQka/n5+Rg4cCDOnz8vmYeEhHCtl3KMBYaIiGRLo9Fg/PjxOHjwoGT+ySef4KuvvhKUiuSABYaIiGQrMjISmzdvlsxatGiB6OhomJqaCkpFcsACQ0REspSQkIA5c+ZIZk5OTti2bRusra0FpSK5YIEhIiLZOXbsGEaMGCGZValSBQkJCahevbqgVCQnLDBERCQrf/zxB4KCgiQrspubmyM2NhaNGjUSmIzk5K0KTFZWFrKzs3WVhYiIyrn79+/Dx8cH6enpkvnKlSvRrl07QalIjkq0kN3hw4exd+9enDx5EikpKdp2bGFhgYYNG6J169bo1q0bPD09yyQsEREZrydPnsDf3x83btyQzKdNmwZfX19BqUiu3lhg8vPzsWHDBqxYsQI3b95ElSpV4O7ujpYtW8LW1hYajQbp6em4du0aVCoV1q5di9q1a2PUqFEYNGgQzM3N9fF1EBGRASssLMTQoUPx888/S+Z9+vTBhAkTBKUiOXtjgWnevDlyc3Ph7++PXr16oXnz5q+9/08//YSdO3di8eLFWL58Oc6dO6ezsEREZJymT5+OvXv3Smbt27dHZGQkFAqFoFQkZ28sMGPGjEHfvn1RoUKFYj2hh4cHPDw8MH36dMTExLx1QCIiMm7//ve/i1wXz9XVFRs3buRWfHqlNx7EO2TIEEl5ycnJKdYTV6hQAUOGDCl9MiIiMnr79u3DlClTJDMHBweoVCpUqVJFUCoyBCU+C6lOnTro2bMnMjIyyiIPERGVE7/88gsGDx4MjUajnVWqVAnx8fGoU6eOwGRkCEpcYAoLC3HkyBH06NEDjx49KnL7Tz/9hPDwcOfWZeEAACAASURBVJ2EIyIi43T9+nX4+fnh6dOn2pmpqSk2bNiAZs2aCUxGhqJU68BMmzYNjx8/Rrdu3fDgwQPJbVevXkVYWJhOwhERkfFJT0+Hr68v7t+/L5lHRESgU6dOglKRoSlVgXF0dMQ333yDvLw8eHt7IzU1Vde5iIjICOXm5iIoKAh//PGHZD527FgMGDBATCgySKVeibdmzZrYt28fTE1N8cknn+D27du6zEVEREZGo9Fg1KhROHbsmGTeq1cvhIaGCkpFhuqtLiVQvXp17Nu3D9bW1ujatSuuX7+uo1hERGRs5s+fD5VKJZm1adMGq1atgokJL81HJfPW3zG2trbYs2cP7O3t4e3tXWSzIBERUUxMDBYvXiyZNWjQALGxscVeZ4zoeSUuMGfOnME///lPyaxKlSrYuXMnHB0dERERoatsRERkBJKSkjBu3DjJrGrVqkhMTISdnZ2gVGToSlxgnJ2dYW9vX2ReuXJl7NixA97e3rC2ttZJOCIiMmznz59Hv379UFBQoJ1VqFABcXFxqFevnsBkZOhKdDXqN6lYsSK2bNmiy6ckIiIDdefOHfj6+iIzM1M7UygUiIqKQqtWrQQmI2Pwxi0w6enppX7yt3ksEREZrszMTPj5+RU5Q3Xu3Lno0aOHoFRkTN5YYJo2bYrZs2fjxo0bxX7S69evY8aMGVxNkYioHCooKMDAgQNx9uxZyXzIkCEYMWKEoFRkbN64C2n16tX46quvsHTpUrRs2RKenp5o3rw56tatC6VSCY1Gg/T0dNy4cQPJyclISkrCmTNn0Lhx4yJXFyUiIuOm0WgwYcIE/Pe//5XMu3TpggULFkChUAhKRsbmjQWmW7du8Pb2xn/+8x/ExsZi5cqVyMnJKfJNqNFoUKFCBXTs2BFffvklvLy8+I1KRFTOLF26FBs3bpTM3N3dsW7dOpiamooJRUapWAfxKhQKdO7cGZ07d0Z+fj7OnDmDP/74Aw8fPgQA2NnZoVGjRnB3d4e5uXmZBiYiInnasWMHZs2aJZk5OjoiPj6eZ6eSzpX4LCRHR0f07duXV5wmIiKtEydO4PPPP5fMbGxsoFKpUKNGDUGpyJiVuMDk5ubijz/+wHfffYeUlBRYW1ujcePGaN26NTcPEhGVQ5cvX0ZgYCDy8vK0M3Nzc8TExKBJkyYCk5ExK9U6MEeOHMGRI0eg0WgA/L2Lyd7eHmPHjsWwYcN0GpCIiOTrwYMH6N27Nx49eiSZL1u2DJ6enoJSUXlQqgJjZWWF2bNn48MPP0Rubi6Sk5Pxf//3f5g6dSpOnTpV5AAuIiIyPk+fPkVAQECRC/lOmTIFAQEBYkJRuVGqAjNixAgMHjxY+3mzZs3Qr18/bNu2DcOHD8e6desQHByss5BERCQvarUaISEhOH36tGQeGBiIL7/8UlAqKk9KfC2kihUromrVqi+9zd/fH/7+/twCQ0Rk5EJDQ7F7927JzNPTE19//TWX0CC9KHGBadSoEfbt2/fK21u2bInLly+/VSgiIpKv6OhorFixQjJr0qQJNm3aBAsLC0GpqLwpcYEZMGAAjhw5gmHDhuHx48dFbj927BjP9yciMlLffvstJk2aJJnVqFEDKpUKSqVSUCoqj0p8DEy/fv2QkpKCFStWYN++fWjfvj1cXV1RoUIFHD58GIcOHULfvn3LIisREQl05swZBAcHQ61Wa2fW1taIj4+Ho6OjwGRUHpXqIN65c+fi008/xapVq5CUlKTdD6pQKNC9e3fMnz9fpyGJiEisP//8E35+fnjy5Il2ZmJigvXr18Pd3V1gMiqvSlVgAKBVq1Zo1aoVNBoNbt68iaysLNSuXRtVqlTRZT4iIhIsPT0dvr6+uHfvnmQeHh6Ozp07C0pF5V2pC8wzCoUCTk5OushCREQyk5eXh759++LixYuS+ejRo7lcBglV4oN4iYiofNBoNBg1ahSOHDkimffs2bPIRRuJ9I0FhoiIXmrBggWIj4+XzFq3bo3Vq1fDxIS/Pkgs4d+BS5YsQfv27eHo6IgGDRrAz88PFy5cEB2LiKhc27NnDxYuXCiZ1a9fH1u3boWVlZWgVET/I7zAHD16FMHBwdi/fz92794NMzMz9OzZs8iFwYiISD8OHz5c5GxSOzs7JCQkvHIldiJ9e+uDeN/Wjh07JJ9HRUXByckJJ0+eRNeuXQWlIiIqny5cuIC+ffuisLBQO7O0tERcXBwaNGggMBmRlPAtMC/KysqCWq3mio5ERHp29+5d+Pr6FlllPSoqCq1btxaUiujlFOnp6RrRIZ43YMAAXLlyBYcOHYKpqekr75eSkqLHVERExu3JkycICQl56enSXF2dRHFxcXnlbcJ3IT1v6tSpOHnyJL777rvXlhfg9V9UaaWkpJTJ85Y15tY/Q83O3PpnCNkLCgoQFBRUpLwEBwdj9uzZBnV1aUN4v1/GUHMD4rLLpsBMmTIFO3bswJ49e+Ds7Cw6DhFRuaDRaDBp0iTs379fMm/Xrh0WLlxoUOWFyhdZFJhJkyZhx44d2Lt3Lxo2bCg6DhFRubFixQqsW7dOMnvvvfcwf/58mJnJ4lcE0UsJ/+6cMGEC4uPjsWXLFiiVSqSmpgL4+wqnlSpVEpyOiMh47dy5EzNmzJDM6tSpg/j4eGRmZgpKRVQ8ws9CWrt2LTIzM9GjRw80atRI+2f58uWioxERGa1Tp04hJCREMrOxsYFKpULNmjUFpSIqPuFbYNLT00VHICIqV65cuYKAgADk5uZqZ2ZmZoiJiYGrq6vAZETFJ3wLDBER6U9aWhp8fHzw8OFDyXzZsmXw9PQUlIqo5FhgiIjKiadPnyIwMBBXr16VzCdNmoTAwEBBqYhKhwWGiKgcUKvVGDZsGE6dOiWZ+/v7Y/LkyYJSEZUeCwwRUTkwa9Ys7Ny5UzL78MMPsWzZMq71QgaJBYaIyMitW7cOy5Ytk8waN26MmJgYWFhYCEpF9HZYYIiIjNj+/fsxceJEyaxGjRpQqVS8aC4ZNBYYIiIjlZycjEGDBkGtVmtnFStWxLZt2+Dk5CQwGdHbY4EhIjJCN2/ehJ+fH7Kzs7UzExMTrFu3Ds2bNxeYjEg3WGCIiIxMRkYGfH19tZdmeWbhwoXo2rWroFREusUCQ0RkRPLy8tCvXz/8/vvvkvnIkSMxZMgQQamIdI8FhojISGg0GowdOxaHDx+WzLt37445c+YISkVUNlhgiIiMxKJFi7B161bJ7P3330dUVBRMTPjjnowLv6OJiIxAXFwcwsLCJLN69eohLi4OVlZWglIRlR0WGCIiA3f48GGMHj1aMrO1tUVCQgKqVasmKBVR2WKBISIyYBcvXkTfvn2Rn5+vnVlaWmLr1q145513BCYjKlssMEREBio1NRU+Pj54/PixZL569Wq0adNGUCoi/WCBISIyQNnZ2fDz88PNmzcl81mzZqFXr16CUhHpDwsMEZGBKSwsRHBwMJKTkyXzgQMHYsyYMYJSEekXCwwRkQHRaDSYPHkyvvvuO8m8U6dOCA8Ph0KhEJSMSL9YYIiIDMjKlSsRHR0tmTVt2hTr16+HmZmZoFRE+scCQ0RkIHbt2oUZM2ZIZrVr14ZKpULlypUFpSISgwWGiMgA/PjjjwgJCYFGo9HOKleuDJVKBQcHB4HJiMRggSEikrlr164hICAAOTk52pmZmRk2b94MNzc3gcmIxGGBISKSsYcPH6J3795IS0uTzCMjI9G+fXtBqYjEY4EhIpKpnJwcBAUF4cqVK5L5hAkT0LdvX0GpiOSBBYaISIbUajWGDx+OEydOSOa+vr6YNm2aoFRE8sECQ0QkQ3PnzsWOHTsks3bt2mH58uVc64UILDBERLKzceNGREZGSmYNGzbEli1bYGlpKSgVkbywwBARyciBAwcwfvx4ycze3h4qlQpKpVJQKiL5YYEhIpKJ3377DQMHDkRhYaF2ZmVlhfj4eDg7O4sLRiRDLDBERDJw69Yt+Pn5ISsrSztTKBRYu3YtWrRoITAZkTyxwBARCZaRkQFfX1/cvXtXMl+wYAG8vb0FpSKSNxYYIiKB8vPzMWDAAFy4cEEyHzZsGEJCQgSlIpI/FhgiIkE0Gg3GjRuHpKQkybxbt26YN2+eoFREhoEFhohIkIiICGzZskUy8/DwwJo1a2BqaiooFZFhYIEhIhJApVIV2cpSt25dxMXFoWLFioJSERkOFhgiIj07evQoRowYIZkplUokJibC3t5eUCoiw8ICQ0SkR5cuXUJQUBDy8/O1MwsLC8TGxsLFxUVgMiLDwgJDRKQn9+7dg4+PDzIyMiTzVatW4R//+IegVESGiQWGiEgPsrOz4e/vjz///FMyDw0NRe/evQWlIjJcLDBERGWssLAQQ4YMwS+//CKZ9+vXD+PGjROUisiwscAQEZWxqVOn4ptvvpHMOnbsiIiICCgUCkGpiAybLArMsWPH4O/vjyZNmkCpVCI2NlZ0JCIinYiLi0NUVJRk5ubmhg0bNsDc3FxQKiLDJ4sCk52dDVdXVyxYsABWVlai4xAR6cSePXsQGRkpmdWqVQsqlQo2NjaCUhEZBzPRAQDAy8sLXl5eAIDhw4cLTkNEspKRAZsTJ2D2xx+ik5TI5cuXsXv+fHyq0WhnVhUqIHTkSNRNTgaSkwWmezPl3bsG954DzK1vGhsboGZNIa8tiwJDRPQyilu3UOnjj1Hlr79ERymx9wCoXhzm5ABTpwpIU3LviA5QSsytX4XNmgHr1gl5bVnsQiIiehnzXbtgYoDlhYjKnsFugUlJSTGo5y1rzK1/hprdkHLXunoVPCqOSL5ycnMBlN3PldetTm2wBaYsltxOSUkxyKW8mVv/DDW7oeW2VColnxc2bAh1gwaC0ryeBsCvycm4c/euZF7d3h4tPTxgaCdLZ2Vno5K1tegYJcbc+mXm7AygbH4nv/G19f6KRETFpVZLPs3390fuF18ICvN6c+fORcS330pmbdq0weLFi/HUzU1QqtK7YmBl9xnmFkDQVl1ZFJisrCxcvXoVAKBWq3Hr1i389ttvsLW1haOjo+B0RCSK4oUCozGR52F7mzdvRkREhGTm4uKCrVu34sGDB4JSERk3Wfw0OHPmDD766CN89NFHePr0KcLCwvDRRx/hq6++Eh2NiER6ocDA1FRMjtc4ePBgkcsBVKtWDQkJCbC1tRWUisj4yWILzIcffoj09HTRMYhIbgoLpZ/LbNn9s2fPYsCAASh8LqeVlRW2bdsG5/9/bAARlQ1ZbIEhInqpF7fAyGgX0u3bt+Hn54fMzEztTKFQYM2aNfDw8BCYjKh8kM9PAyKiF8m0wDx+/Bi+vr64c+eOZD5//nx8+umnglIRlS/y+GlARPQyzy3DD0AWx8Dk5+dj4MCBOH/+vGQeEhLCS6EQ6RELDBHJl8y2wGg0GowfPx4HDx6UzD/55BOedECkZywwRCRfLx7EK7jAREZGYvPmzZJZixYtEB0dDVMZbB0iKk9YYIhItuS0DkxiYiLmzJkjmTk5OWHbtm2wNsAVVIkMHQsMEcnXi7uQBJ1GfezYsSLHt1SpUgUJCQmoXr26kExE5R0LDBHJlwwWsktJSUFQUBDy8vK0M3Nzc8TGxqJRo0Z6z0NEf2OBISL5EnwMzP3799G7d+8iC22uXLkS7dq102sWIpJigSEi+XrxNGo9FpgnT54gICAAN27ckMynTZsGX19fveUgopdjgSEi+RJ0GnVhYSGGDh2Kn376STLv06cPJkyYoJcMRPR6LDBEJF+CjoGZMWMG9u7dK5m1b98ekZGRUMjsekxE5RULDBHJl4DTqKOiorBq1SrJzNXVFRs3boS5uXmZvz4RFQ8LDBHJlkLPV6Pet28fJk+eLJk5ODhApVKhSpUqZfraRFQyLDBEJF96PAbml19+weDBg6F57sDhSpUqIT4+HnXq1Cmz1yWi0mGBISL50lOBuX79Ovz8/PD06VPtzNTUFBs2bECzZs3K5DWJ6O2wwBCRfOnhIN709HT4+fnh/v37knlERAQ6deqk89cjIt1ggSEi+SrjLTC5ubno06cPLl26JJmPHTsWAwYM0OlrEZFuscAQkXyVYYHRaDQYNWoUjh49Kpn36tULoaGhOnsdIiobLDBEJF9lWGC++uorqFQqyaxNmzZYtWoVTARe9ZqIiof/SolIthQvrgOjo2NgYmJiEB4eLpk1aNAAsbGxqFChgk5eg4jKFgsMEcnXi1tgdLAOTFJSEsaNGyeZVa1aFYmJibCzs3vr5yci/WCBISL50vHVqM+fP4/+/fujoKBAO6tQoQLi4uJQr169t3puItIvFhgiki8dXo367t278PX1xePHj7UzhUKBqKgotGrVqtTPS0RisMAQkXzp6CDezMxM+Pr64vbt25L53Llz0aNHj9KmIyKBWGCISL50sJBdQUEBBg0ahLNnz0rmQ4YMwYgRI94mHREJxAJDRPL1lsfAaDQaTJw4EQcOHJDMu3TpggULFkBRxheHJKKywwJDRPL1lruQli1bhg0bNkhm7u7uWLduHUzL4LIERKQ/LDBEJFtF1oEpwRaTHTt2YObMmZKZo6Mj4uPjYW1trZN8RCQOCwwRyVcpj4E5ceIEhg0bJpnZ2NhApVKhRo0aukpHRAKxwBCRfJViF9Lly5cRGBiI3Nxc7czc3BwxMTFo0qSJrhMSkSAsMEQkXyUsMA8ePICPjw8ePXokmS9btgyenp66TkdEArHAEJF8laDAPH36FAEBAbh27ZpkPmXKFAQEBJRFOiISiAWGiOSrmAVGrVYjJCQEp0+flswDAwPx5ZdfllU6IhKIBYaI5KuYB/GGhoZi9+7dkpmnpye+/vprrvVCZKRYYIhIthQvLGSneckWmOjoaKxYsUIya9KkCTZt2gQLC4syzUdE4rDAEJF8vbgF5oWtKd9++y0mTZokmdWoUQMqlQpKpbKs0xGRQCwwRCRfr7kadXJyMoKDg6F+ruRYW1sjPj4ejo6O+kpIRIKwwBCRfL3iGJg///wTfn5+ePLkifYmExMTrF+/Hu7u7vpMSESCsMAQkXy95Cyk9PR0+Pr6IjU1VXJTeHg4OnfurMdwRCQSCwwRydcLB/HmFRSgb9++uHjxomQ+evRoBAcH6zMZEQnGAkNE8vXCFpip06fjyJEjklnPnj0xa9YsPYYiIjlggSEi+XqhwGzfuVPyeevWrbF69WqYFOMaSURkXGTzr37t2rVo1qwZatSoAU9PTxw/flx0JCISTPFCgXl+h1L9+vWxdetWWFlZ6TcUEcmCmegAALBjxw5MnjwZERER+OCDD7B27Vr4+Pjg5MmTejsdUl1QgPysLOQ+fqyX19Ml5tY/Q81uaLk1hYV4fuWXZ3XGzs4OiYmJqFq1qohYRCQDsigwK1euRGBgIPr37w/g77MJDh48iPXr12PmzJl6yXBh+XL8Y/ZsvbyWrlUXHaCUDDU3YLjZDTX3M2oAlpaWiIuLQ/369UXHISKBhO9CysvLQ3JyMjp06CCZd+jQAadOnRKUiojkSA0gKioKrVu3Fh2FiAQTvgUmLS0NhYWFsLe3l8zt7e1x7969Vz4uJSVFpzkePHig0+cjIt26DWDIqFFwc3PT+b//smZoeZ9hbv0y1NxA2WV3cXF55W3CC8wzL14xVqPRvPYqsq/7okojr3p15Or0GYlIV26bmeFMcDBmz5ljcFeXTklJ0fnPK31gbv0y1NyAuOzCC0zVqlVhampaZGvLgwcPimyVKUtuY8bg7CefGOQ3kKF+4xtqbsBwsxtq7ocpKfjYAHMTUdkRfgyMhYUF3N3dkZSUJJknJSVxPzcRERG9lCI9PV3z5ruVrR07diAkJAQRERFo3bo11q9fjy1btuDEiRNwcnISHY+IiIhkRvguJADo1asXHj58iPDwcKSmpqJJkyZQqVQsL0RERPRSstgCQ0RERFQSwo+BISIiIiopFhgiIiIyOCwwREREZHBYYF7C29sbSqVS8mfQoEGiYxWbRqPBZ599BqVSiV27domOUyyjR4+Gu7s7atasiQYNGiAgIACXLl0SHeu1Hj16hIkTJ+L9999HzZo14ebmhi+++AIPHz4UHe2NNm7ciG7dusHJyQlKpRI3btwQHemVDPFK9ceOHYO/vz+aNGkCpVKJ2NhY0ZHeaMmSJWjfvj0cHR3RoEED+Pn54cKFC6JjFUt0dDTatm0LR0dHODo6olOnTti/f7/oWCUWEREBpVKJiRMnio7yWmFhYUV+RzZs2FDvOVhgXiEoKAiXLl3S/omMjBQdqdhWrFgBU1NT0TFKpHnz5li1ahVOnTqF7du3Q6PRoGfPnsjPzxcd7ZXu3r2Lu3fvYvbs2Th+/DiioqJw/PhxBAcHi472Rk+ePEGHDh0wefJk0VFe69mV6sePH48ffvgBrVq1go+PD27evCk62mtlZ2fD1dUVCxYsgJWVleg4xXL06FEEBwdj//792L17N8zMzNCzZ088evRIdLQ3qlWrFmbPno3Dhw8jKSkJH330EYKCgnDu3DnR0Yrt9OnT2LRpE9zc3ERHKRYXFxfJ70gR/7HgWUgv4e3tDVdXV4SHh4uOUmJnzpxBnz59cOjQIbi4uGDTpk3o0aOH6Fgldu7cObRr1w6nT582qJVj//Of/8DPzw83btyAjY2N6DhvdObMGbRv3x6//vor6tatKzpOER07doSbmxuWLVumnbVo0QI9evTQ25Xq31bt2rWxaNEiBAUFiY5SIllZWXByckJsbCy6du0qOk6JOTs7Y+bMmRg4cKDoKG+UkZEBT09PLF26FIsWLZL975+wsDDs3r0bJ06cEJqDW2BeYfv27ahfvz4++OADTJ8+HZmZmaIjvVFmZiaCg4MRGRmp18sw6Fp2djZiY2NRp04dg1sLKDMzE5aWlqhYsaLoKAaPV6oXKysrC2q1GkqlUnSUEiksLMT27duRnZ2NVq1aiY5TLGPHjkWPHj3g6ekpOkqxXb9+HU2aNEGzZs0waNAgXL9+Xe8ZZLGQndz4+PjA0dERNWvWxMWLFzF79mycO3cOO3fuFB3ttb744gt07NgRXl5eoqOUytq1azFz5kxkZ2fDxcUFu3fvhqWlpehYxZaeno758+ejX79+MDPjP623Vdor1ZNuTJ48GU2bNjWYEnD+/Hl4eXkhJycH1tbW2LJli0Hsjtm0aROuXr2KqKgo0VGKzcPDA6tWrYKLiwsePHiA8PBweHl54eTJk7Czs9NbjnLzU3bevHlYvHjxa++zZ88efPjhhxgwYIB25ubmBmdnZ3Ts2BHJyclwd3cv46RSxc19+/ZtnDt3rsg1pUQqyXsO/F0c27dvj7/++gvLly9H//79sX//fr1vzShpbuDvrUYBAQFwcHDAnDlzyjriS5UmtyEo6ZXq6e1NnToVJ0+exHfffWcwx9O5uLjgyJEjyMjIwO7duzFs2DDs3bsXrq6uoqO9UkpKCubMmYNvv/0WFhYWouMUW6dOnSSfe3h4wN3dHVu3bsXIkSP1lqPcHAOTlpaGtLS0196nTp06L/1lqVarYW9vj+joaPTq1ausIr5UcXOPHz8e27Ztg4nJ//YKFhYWwsTEBK1atcJ3331X1lGLeJv3PC8vD87OzliyZAn8/f3LKuJLlTR3VlYWfHx8AAAJCQmoVKlSmWd8mdK833I+BiYvLw8ODg5Yt24devbsqZ1PmDABFy5cwDfffCMwXfEZ2jEwU6ZMwY4dO7Bnzx4hZ5boSo8ePeDo6IgVK1aIjvJKsbGxGDFihKQkFhYWQqFQwMTEBHfu3DGYrdDdunVDw4YNsWTJEr29ZrnZAlO1alVUrVq1VI89f/48CgsLUaNGDR2nerPi5p4xYwZGjRolmbVt2xZz586Ft7d3WcV7rbd5zzUaDTQaDfLy8nSc6s1KkjszMxM+Pj7QaDRITEwUVl6At3u/5ej5K9U/X2CSkpLQvXt3gcmM16RJk7Bjxw7s3bvXoMsL8Pd/PEX8/CgJb29vNG/eXDIbMWIEGjRogC+++MJgtsrk5OQgJSVF71t3y02BKa5r165BpVLBy8sLdnZ2uHTpEqZPn45mzZrhgw8+EB3vlWrVqoVatWoVmdepUwfOzs76D1QCV69exe7du/HPf/4TVatWxZ07dxAZGQkLCwt07txZdLxXyszMRK9evZCZmYnY2Fg8efIET548AQDY2trK+odPamoqUlNTcfnyZQDApUuXkJGRAUdHR9ja2gpO9z8jRoxASEgIWrZsqb1S/V9//SX7M0uysrJw9epVAH//Ir116xZ+++032NrawtHRUXC6l5swYQLi4+OxZcsWKJVKpKamAgCsra2FFvPimDVrFry8vFC7dm1kZWUhMTERR48ehUqlEh3ttZ6tofK8ihUrwtbWVta7vqZPn44uXbqgTp062mNgnjx5goCAAL3mYIF5gbm5OQ4fPox///vfyM7ORu3ateHl5YXJkycbzL5gQ2NhYYGjR49ixYoVyMjIQPXq1dG2bVscOHBAyFav4kpOTsbp06cBAC1btpTcJvdjTdavX4+FCxdqP/f19QUArFy5Ula7Ogz1SvVnzpzBp59+qv08LCwMYWFhCAgIwOrVqwUme7W1a9cCQJFlFyZNmoQpU6aIiFRsqampGDp0KO7duwcbGxu4ubkhMTERHTt2FB3NKN25cweDBw9GWloaqlWrBg8PDxw4cEDv/y7LzTEwREREZDy4DgwREREZHBYYIiIiMjgsMERERGRwWGCIiIjI4LDAEBERkcFhgSEiIiKDwwJDREREBocFhoiIiAwOCwwREREZHBYYIiIiMji8FhIRydaLF7p73q+//oq6devqMQ0RyQkLDBHJVlRUVJHZ3Llz8eDBA9lfIZmIyhYLDBHJlp+fn+TziIgI3Lp1C6tXr0bVqlUFpSIiOeAxMERkEA4cOID58+dj6NChCAgIEB2HiARTpKena0SHICJ6nStXHZUI0AAAAPdJREFUrqBDhw5wdXXFnj17YGbGjcdE5R0LDBHJWlZWFj7++GM8fvwYhw4dQvXq1UVHIiIZ4H9jiEi2NBoNPv/8c1y7dg379u1jeSEiLRYYIpKtxYsXY+/evVi2bBk8PDxExyEiGeEuJCKSpQsXLqBdu3Zo2LAhxo0bV+T2bt26wdraWkAyIpIDboEhIllKS0uDWq3GxYsXERISUuT2X3/9lQWGqBzjFhgiIiIyOFwHhoiIiAwOCwwREREZHBYYIiIiMjgsMERERGRwWGCIiIjI4LDAEBERkcFhgSEiIiKDwwJDREREBocFhoiIiAwOCwwREREZnP8H1lbxm6SRl4AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plot_activation(torch.relu)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0., 0., 3.])"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummy_z = torch.tensor([-3., 0., 3.])\n",
    "F.relu(dummy_z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0., 0., 3.])"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nn.ReLU()(dummy_z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0., 0., 3.])"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummy_z.clamp(min=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Leaky ReLU"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\Large\n",
    "\\begin{aligned}\n",
    "\\sigma(z) =&\n",
    "\\begin{cases}\n",
    "z,\\ \\text{if } z \\ge 0\n",
    "\\\\\n",
    "0.01z,\\ \\text{if } z < 0\n",
    "\\end{cases}\n",
    "\\\\\n",
    "\\text{or}&\n",
    "\\\\\n",
    "\\sigma(z)=&\\text{max}(0,z)+0.01\\ \\text{min}(0,z)\n",
    "\\end{aligned}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plot_activation(nn.LeakyReLU(), name='Leaky ReLU')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([-0.0300,  0.0000,  3.0000])"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummy_z = torch.tensor([-3., 0., 3.])\n",
    "F.leaky_relu(dummy_z, negative_slope=0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([-0.0600,  0.0000,  3.0000])"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nn.LeakyReLU(negative_slope=0.02)(dummy_z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parametric ReLU (PReLU)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\Large\n",
    "\\begin{aligned}\n",
    "\\sigma(z) =&\n",
    "\\begin{cases}\n",
    "z,\\ \\text{if } z \\ge 0\n",
    "\\\\\n",
    "az,\\ \\text{if } z < 0\n",
    "\\end{cases}\n",
    "\\\\\n",
    "\\text{or}&\n",
    "\\\\\n",
    "\\sigma(z)=&\\text{max}(0,z)+a\\ \\text{min}(0,z)\n",
    "\\end{aligned}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lkJ6eDk9PT1hbW2Pv3r2oVq0arl69CgDw8fHB7du3cezYMURGRgIALC0t82y/f//+GDp0KJKTk9Xvx8mTJ/HkyRP069cPwL/X0Rk/fjzq16+P169fY82aNfD398eZM2dgbGyMX3/9FZ06dcLhw4dRv359GBsb5/t32bp1KzZt2oR169ahSZMmOHDgAIYMGYLffvsNDRs2VD9v2bJlWLJkCdauXYvVq1dj5MiRuHr1KipUqKDx+0dEpK/S09MxYMAAnDx5UjB3cXFBeHg4qlatKlIyzbHASFBQUBD8/f0BAG3btoWZmRm+//57+Pj4ICQkBE+fPsXx48dRuXJlAFCfu5+RkaG+xL6NjU2B2+/cuTMsLCwQERGBoUOHAgAOHTqEDh06qF/n4+MjeM2WLVvg4OCA8+fPw93dXb1vKyurd+5r8+bNmDx5Mvz8/AAA8+fPR3R0NDZv3oxvvvlG/byJEyeiR48eAICFCxciODgYV69e5YJgIqJCevnyJfr3749Tp04J5q6uroiIiECVKlVESlY0/AhJYu7evYszZ86oj4TIZDL0799f/THSlStX4Obmpi4QRWFkZITevXvj0KFDAP5dpR4REYH+/furn/PPP/9g9OjRaNy4MRwcHFCnTh0olUo8ePCg0PtJTU3F48eP0bp1a8Hc3d0df//9t2Dm5uam/v2bw5vPnj3T+O9GRKSPUlNT4efnl6e8NGjQAAqFQnLlBeARGMkJCgpCbm4u6tevr56pVCoAwIMHD9S/L64BAwagW7duePToEc6dO4fs7Gx4eXmpH/f394ednR2+/PJL2NnZwcjICK1atUJWVlaJ7P/tK+mWK1cuz2Ml9XclIirLUlJS0K9fP8TExAjmjRo1QlhYGCpVqiRSsuJhgXlLYdekZGRk6PzGiDk5Ofjuu++waNGiPKdPjxs3Dvv27UOjRo1w8OBBPH/+PN+jMMbGxsjNzX3vvpo3b45atWrh8OHDOHv2LDw9PdXrTV68eIGbN29i9erVaN++PQDg0qVLyMnJEewHwDv3ZWlpCTs7O5w+fRodOnRQz0+dOoW6deu+NyMREb1bcnIy+vbti/PnzwvmTZs2RWhoqM7XfZYkFhgJOXbsGJ4/f45hw4blORW5b9++2LlzJ06fPo3169dj0KBBWLhwIapVq4YbN26gQoUKaNmyJWrUqIH4+HhcunQJDg4OqFChAkxMTPLdn5+fH4KCgnD//n3s3btXPZfL5ahcuTKCgoJgb2+PR48eYeHChYI7P1tbW8PMzAy//PILatSoARMTE1SsWDHPPqZMmYKAgAA4OTmhcePGOHDgAE6dOoXffvutZN40IiI9lZSUhN69e+PSpUuCeYsWLRASEpLv92Qp4RoYCdmzZw/atWuX73VUfH19ER8fjzNnzuDo0aOws7ODv78/3N3dERAQoP7YxdvbG127doWPjw+cnJwQEhJS4P4GDBiA2NhYWFpaomPHjuq5gYEBAgMDcf36dbi7u2PWrFmYP3++oAgZGRlh5cqV2LNnD+rVq4eBAwfmu4/x48djypQpWLRoEdzd3XH06FEEBQUJzkAiIiLNvHjxAj4+PnnKS6tWrXD48GHJlxcAkCUnJ+vlQoKUlJRi/QcU4yOk4tK3zMX9b1wcsbGxcHZ2FmXfRcXMuiHFzIA0c+tr5sTERPj4+OD69euCubu7Ow4ePAgLC4tibf9tYr3PPAJDRERURjx79gze3t55ykvbtm0REhJS4uVFTCwwREREZUBCQgJ69eqFGzduCObt27fHwYMHYW5uLlIy7WCBISIikrjHjx/Dy8srzzW0OnbsiODgYJ3c607XWGCIiIgk7NGjR/Dy8kJsbKxg3qVLF+zfv79MlheABYaIiEiyHjx4AE9PT9y5c0cw7969O/bu3QszMzORkmkfCwwREZEE3b9/H56envjnn38E8x49eiAoKEhyZ51qigWGiIhIYuLi4uDp6Yl79+4J5l5eXti9e3eBFygtS1hgiIiIJOSff/6Bl5cX4uPjBXMfHx98++236lu5lHUsMERERBJx584deHl54cGDB4L5m9vJ/PfGt2UdCwwVyqxZs+Dp6an+84QJEzBgwAARExER6ZfY2Fh4eXnh4cOHgnn//v2xbds2wf3o9AELjEQ9ffoU8+bNQ9OmTWFjY4MPPvgA3bp1w7Zt25CWlqb1/a9YsQLbtm0r0W3++eefkMvleP78eYlul4hI6m7evAkvLy88fvxYMPf398fWrVv1rrwAvBu1JN27dw8fffQRLCwsMH/+fLi5uUGpVOL27dsIDg6GlZUV/Pz88rwuKyurxFall4UbgRERScFff/0Fb29vPHv2TDAfPHgwNmzYAENDQ5GSiYtHYCRoxowZMDAwwIkTJ9C3b1/Uq1cPrq6u8Pb2xv79+9GvXz8AgFwux/bt2zF48GBUq1YNy5cvR25uLiZPnoyGDRvC1tYWTZs2xYYNG6BUKtXbz83Nxeeffw5HR0c4Ojpi7ty5yM3NFWR4+yMklUqFDRs2oHHjxrC1tYWHhwcOHDigfvzevXuQy+UIDw+Hr68v7Ozs0KpVK5w4cUL9eK9evQAATk5OkMvlmDBhgtbeQyIiKbh27Rq8vLzylJdhw4Zh48aNelteAB6ByaOiXF6455XQ/lKSkzV6flJSEn755RcsXLiwwPtayGQy9e9XrlyJhQsXYtmyZcjMzIRSqYSdnR127dqFypUr48KFC/jkk09QqVIlDB06FACwefNmBAUFYcOGDXBzc8P27dtx6NAhNGzYsMBcy5YtQ3h4ONasWYMPPvgAMTEx+OSTTyCXy9G9e3fB85YsWYK1a9di9erVGDlyJK5evQp7e3sEBQVh6NChOH36NCpVqlTmr2FARPQuV65cga+vL168eCGYjxw5EmvWrIGBgX4fg2CBkZg7d+5ApVLhgw8+EMxdXV2RkpIC4N8FXevXrwcA9O7dW11MMjIyUK5cOcyfP1/9OkdHR1y+fBmHDx9WP2/r1q2YOnUqevfuDeDfEvTrr78WmCk9PR1btmxBaGgoPDw8AAA1a9bE+fPnsWPHDkGBmThxInr06AEAWLhwIYKDg3H16lW4u7ujUqVKAABra2tUrlxZnZmISN9cunQJvr6+SH7rh9wxY8Zg1apVgh9U9RULTBnx/fffQ6lU4pNPPhH8o9+kSZM8zw0MDERQUBDi4+ORkZGB7OxsODg4AABSUlLw5MkTtGjRQv18AwMDNGvWLM/K9zdu3ryJjIwM9OvXT/BFlZ2djRo1agie6+bmpv69nZ0dAOQ5NEpEpM8uXLiA3r17q38ofWP8+PEICAhgefn/JF9g1q5di6VLl2LMmDFYvXq12HG0rnbt2pDJZHlu2lWzZk0AyHPTrrc/ZgoNDcW8efOwdOlStGzZEpaWlti+fTsiIyOLnOnN+pnvvvtOXYTeeHtl/H+vUfDmi1ClUhV530REZcnVq1cxbdo0pKamCuaTJ0/G0qVLWV7+Q9IFJiYmBrt37xb8VF9chV2TkpGRIcoaDSsrK3Tq1Anbt2/H2LFjUaFCBY1ef+rUKTRr1gxjx45Vz/57H42KFSvC1tYW586dQ4cOHQD8WzAuXLgAGxubfLdZt25dmJiYID4+Xv2aonhz9ci3FwwTEemDM2fOYMqUKUhPTxfMp02bhkWLFrG8vEWyK4BSUlIwZswYbNq0CfJCLrwtK9auXQulUokPP/wQISEh+Pvvv3H79m2EhITg2rVr71yV/sEHH+DKlSs4fvw47ty5g1WrViE6OlrwnPHjx2PDhg0IDw9HbGws5s6di4SEhAK3aWFhgSlTpmDBggXYs2cP7t69iytXriAwMBC7du0q9N/LwcEBMpkMx44dQ2Jiok6uZ0NEVBqcOnUKffv2zVNeZs6cyfJSAMkWmGnTpsHHx6dYP/FLVc2aNfHHH3+gc+fO+OKLL9C+fXt06NABW7ZswahRoxAQEFDga0eMGAFfX1+MHj0aHTt2xP379zFp0iTBcyZPnoxBgwZhypQp6Ny5M5RKZb7Xlfmv+fPnY+7cudi8eTNat26N3r17IyIiAo6OjoX+e1WrVg3z5s3DsmXL4OzsjFmzZhX6tUREUnXy5En069cvzw9tc+bMwfz581leCiBLTk6W3AKE3bt3IzAwEMePH4exsTE8PT3h6upa4BqYt9eLAICpqSmsra21HZVE9OzZM57FRESlWkxMDD799FNkZmYK5uPGjcPo0aNFSlV6ODs7F/iY5NbAxMbGYsmSJfjhhx8KfcfN/N6AlJSUYq1hEWsNTHHoW2ZLS8s8i4p1JTY29p1feKURM+uGFDMD0sxd2jOfOHEC06dPz1NeFi5ciOnTp4uUSnNivc+SKzBnz57F8+fP4e7urp7l5uYiOjoagYGBePToEUxMTERMSERE9G4///wzBg0alKe8TJ06VVLlRUySKzCenp55rm0yadIkODk5Yfr06YU+KkNERCSGn376CYMHD0ZWVpZgvmzZMsGFP+ndJFdg5HJ5nrOOypcvj0qVKsHV1VWkVERERO/3ww8/YOjQocjOzhbMV6xYgfHjx+e7ZpPyJ9mzkIiIiKREoVDkW15Wr16N8ePHi5RKuiR3BCY/R48eLdLrVCoVT08ro3h1XyIqTcLDwzFq1Cjk5OQI5uvXr8eIESNESiVtensExtzcHMnJyfyHrgxSqVRITk4u8G7dRES6FBoaipEjRwrKi0wmw8aNG1leiqFMHIEpCiMjI1hYWOS530RhpaamwtLSsoRTaZc+ZbawsMhzHyYiIl07dOgQxo0bp75nHPBvedm8eTMGDRokYjLp0+vv8EZGRqhYsWKRXvv06VPRrjFSVMxMRKQ7wcHBmDhxoqC8GBgYYOvWrRgwYICIycoGvS4wRERE2rBv3z5MnjxZsEzBwMAA33zzDfr16ydisrJDb9fAEBERaUNQUFCe8mJoaIidO3eyvJQgFhgiIqIS8u2332Lq1KmC8mJkZITAwED07t1bxGRlDwsMERFRCdi+fTs+/fRTwaxcuXLYtWsXfHx8REpVdrHAEBERFdPWrVsxa9YswczY2BhBQUHw8vISKVXZxgJDRERUDJs3b8a8efMEMxMTE+zduxc9evQQKVXZxwJDRERURBs2bMDnn38umJmYmGD//v3o1q2bSKn0A0+jJiIiKoK1a9di6dKlgpmpqSmCg4Px4YcfihNKj7DAEBERaWjlypUICAgQzMqXL4/vvvsOHTp0ECmVfmGBISIiKiSVSoWAgACsWrVKMDc3N8eBAwfQtm1bkZLpHxYYIiKiQlCpVPjiiy+wZs0awbxChQo4dOgQ3N3dRUqmn1hgiIiI3kOlUmHx4sX48ssvBXMLCwscPnwYLVu2FCmZ/mKBISIiegeVSoUFCxZg8+bNgrmlpSVCQ0PRvHlzkZLpNxYYIiKiAqhUKsybNw9ff/21YF6xYkWEhYWhSZMmIiUjFhgiIqJ8qFQqzJ49G9u3bxfM5XI5wsLC0LhxY5GSEcACQ0RElIdSqcTMmTMRGBgomFtZWSEsLAwNGzYUKRm9wQJDRET0H0qlEtOmTUNQUJBgXqVKFYSHh8PNzU2kZPRfLDBERET/X25uLqZMmYL9+/cL5tbW1oiIiICLi4tIyehtLDBERET4t7xMnDgRBw4cEMxtbGwQERGBunXripSM8sMCQ0REei8nJwcTJkzAoUOHBHM7OztERETA2dlZpGRUEBYYIiLSazk5ORg7dixCQ0MF8+rVq0OhUKB27doiJaN3YYEhIiK9lZ2djdGjRyM8PFwwt7e3R2RkJGrWrClOMHovFhgiItJLWVlZGDlyJCIjIwXzGjVqQKFQwNHRUaRkVBgsMEREpHcyMzMxbNgw/Pjjj4K5o6MjFAoFatSoIVIyKiwWGCIi0isZGRkYOnQofvrpJ8G8Vq1aUCgUsLe3FykZaYIFhoiI9Mbr168xZMgQ/Pzzz4K5k5MTFAoFqlWrJlIy0hQLDBER6YVXr15h0KBBOHHihGBep04dREREwNbWVqRkVBQsMEREVOalp6fj448/xh9//CGY16tXD+Hh4bCxsREpGRUVCwwREZVpaWlpGDBgAKKiogRzV1dXhIeHw9raWqRkVBwsMEREVGa9fPkS/fv3x9C7mX8AACAASURBVKlTpwTz+vXrIzw8HJUrVxYpGRWXgdgBNLV9+3Z4eHjAwcEBDg4O6Nq1K44dOyZ2LCIiKmXS0tLQr1+/POWlYcOGiIiIYHmROMkdgalWrRoWL14MJycnKJVKfPfddxg0aBB+++031K9fX+x4RERUCqSkpGDKlCm4du2aYN6kSRMcOXIEcrlcpGRUUiRXYDw9PQV/XrBgAXbu3ImYmBgWGCIiQnJyMvr06ZOnvDRr1gyHDx9meSkjJFdg/is3NxdhYWFIT09Hy5YtxY5DREQiS0pKgq+vLy5fviyYt2zZEocOHULFihVFSkYlTZIF5vr16+jWrRsyMjJgbm6OvXv3ws3NTexYREQkoufPn8PX1xdXr14VzFu3bo1Dhw7BwsJCpGSkDbLk5GSV2CE0lZWVhQcPHiAlJQURERHYvXs3IiMj4erqmu/zY2NjdZyQiIh0KSkpCRMnTsTt27cF8yZNmuDLL79E+fLlRUpGxeHs7FzgY5IsMG/z8fGBg4MDNm/erLN9xsbGvvONLY2YWXekmJuZdUOKmYHSnfvp06fw8fHBX3/9JZg3b94c4eHhMDc3FymZ5krz+1wQsTJL7jTq/CiVSmRlZYkdg4iIdOzJkyfw8vLKU14+/PBDrF+/XlLlhTQjuTUw//vf/9CtWzdUr14daWlpCAkJwcmTJ3Hw4EGxoxERkQ49evQI3t7eeT426tSpE/bt24cHDx6IlIx0QXIFJiEhAWPHjsXTp09haWkJNzc3hISEoHPnzmJHIyIiHXn48CF69eqFu3fvCuZdu3bFnj17YGpqKlIy0hXJFZitW7eKHYGIiEQUHx+PXr16IS4uTjDv3r07goKCYGJiIk4w0qkysQaGiIj0w7179+Dp6ZmnvPTs2RN79uxhedEjLDBERCQJcXFx8PT0xP379wVzb29v7N69G8bGxiIlIzGwwBARUal39+5deHl55VmY27t3b+zcuRPlypUTKRmJhQWGiIhKtdu3b+dbXvr164ft27ezvOgpFhgiIiq1bt26BS8vLzx69Egw79+/P77++msYGUnuXBQqISwwRERUKv3999/w8vLCkydPBPOPP/4YW7duZXnRcywwRERU6ty4cQNeXl54+vSpYD5kyBBs2bIFhoaGIiWj0oIFhoiISpWrV6+iV69eSExMFMyHDx+ODRs2wMCA/3QRCwwREZUily9fhre3N54/fy6Yjx49GuvWrWN5ITX+n0BERKXCpUuX4O3tjaSkJMF83LhxWL16NcsLCfD/BiIiEt358+fh7e2NlJQUwXzixIlYsWIFZDKZSMmotGKBISIiUcXExKB3795ITU0VzKdOnYovvviC5YXyxQJDRESiOX36NPr06ZOnvEyfPh2LFy9meaEC8SR6IiISRVRUFPr374/09HTBfNasWfjss89YXuidWGCIiEjn/vzzTwwYMACvXr0SzOfOnYu5c+eKlIqkhAWGiIh06vfff4e/vz9ev34tmM+fPx+zZs0SKRVJDQsMERHpzK+//oqBAwciIyNDMF+0aBE+/fRTkVKRFLHAEBGRThw/fhyDBw9GZmamYL506VJMmTJFpFQkVSwwRESkdT/++COGDh2KrKwswXz58uWYOHGiSKlIylhgiIhIq44ePYrhw4cjOztbMF+1ahXGjh0rUiqSOhYYIiLSmoiICIwcORI5OTmC+dq1azFq1CiRUlFZwAJDRERaERYWhlGjRiE3N1cw37BhA4YNGyZSKioreCVeIiIqcYcPH85TXmQyGTZt2sTyQiWCR2CIiKhEHTx4EOPHj4dSqVTPZDIZvvrqK3z88cciJqOyhEdgiIioxOzfvx/jxo0TlBcDAwNs27aN5YVKVLEKTFpaWp57WBARkX7as2cPJk2aBJVKpZ4ZGhpi+/bt6N+/v4jJqCzS6COk33//HZGRkTh9+jRiY2PV5/MbGxujTp06aNWqFby8vNChQwethCUiotJp165dmDZtmmBmaGiInTt3wtfXV6RUVJa9t8BkZ2fj22+/xebNmxEfH4+KFSuicePGaNasGSpVqgSVSoXk5GT8888/OHjwIHbs2IHq1atjypQpGDlyJMqVK6eLvwcREYlk586dmDFjhmBmZGSEwMBAeHt7i5SKyrr3FpgmTZogMzMT/v7+6NOnD5o0afLO5587dw5hYWFYs2YNNm3ahGvXrpVYWCIiKl22bduGOXPmCGblypXDrl274OnpKVIq0gfvLTCffPIJhgwZAlNT00JtsHnz5mjevDk+//xz7Nmzp9gBiYiodNqyZQvmz58vmBkbGyMoKAgfffSRSKlIX7x3Ee+YMWME5eXtO4gWxNTUFGPGjCl6MiIiKrU2bdqUp7yYmJhg3759LC+kExqfhWRvbw9fX1+kpKRoIw8REZVy69evx4IFCwQzU1NTfPfdd+jatatIqUjfaFxgcnNz8eeff8LHxwdJSUl5Hj937hxWr15dIuGIiKh0WbNmDRYvXiyYmZmZ4cCBA+jUqZNIqUgfFek6MPPnz0dqaiq8vLyQmJgoeOzu3bsICAgokXBERFR6rFixAsuWLRPMypcvj4MHD/LyGaRzRSowDg4O+P7775GVlQVPT08kJCSUdK4CrVu3Dh07doSDgwOcnJwwYMAA3LhxQ2f7JyLSNyqVCl9//TVWrFghmJubmyMkJATt2rUTKRnpsyJfidfW1hZHjx6FoaEhevbsiYcPH5ZkrgKdPHkSo0aNwrFjxxAREQEjIyP4+vrm+3EWEREVj0qlwtKlS7Fz507B3MLCAocPH4aHh4dIyUjfFetWAlWrVsXRo0dhbm6OHj16IC4uroRiFSw0NBSDBw+Gq6sr3NzcsG3bNiQmJuL06dNa3zcRkT5RqVRYtGgR1q1bJ5hbWlri8OHDaN26tUjJiErgZo6VKlWCQqGAtbU1PD09cevWrZLIVWhpaWlQKpWQy+U63S8RUVmmUqkwf/58bNy4UTC3tLTEkSNH0LJlS5GSEf1LlpycrHr/0/5PXFwczM3NYW1tLZi/fPkSfn5+OHPmDGQyGV68eFGiQQsyfPhw3LlzB7/99hsMDQ3zfU5sbKxOshARlQUqlQpr167FgQMHBHNLS0ts3rwZLi4uIiUjfePs7FzgYxoXmHd59eoVxo4di99//x3x8fEltdkCffbZZwgNDcWPP/6ImjVran1//xUbG/vON7Y0YmbdkWJuZtaN0p5ZqVRi1qxZeda8VKxYEREREWjUqJFIyTRX2t/r/DBz4Wl0N+r3KV++PPbu3VuSmyzQvHnzEBoaCoVCofPyQkRUFimVSkyfPh27du0SzCtXroyNGzdKqrxQ2ffeApOcnFzk9SXFee27zJkzB6GhoYiMjESdOnVKfPtERPpGqVTik08+yXMPuypVqiAiIgLlypUTKRlR/t67iLdBgwZYvHgx7t27V+iNxsXFYcGCBWjYsGGxwuVn5syZ2L9/P3bs2AG5XI6EhAQkJCQgLS2txPdFRKQPcnNzMXny5DzlpWrVqoiMjISrq6tIyYgK9t4jMFu3bsXy5cuxYcMGNGvWDB06dECTJk3g6OgIuVwOlUqF5ORk3Lt3D5cuXcKJEydw8eJF1KtXD1u3bi3xwDt27AAA+Pj4COZz5szBvHnzSnx/RERlWW5uLiZMmICDBw8K5ra2toiIiOBRbiq13ltgvLy84OnpiZ9++gn79u3Dli1bkJGRAZlMJnieSqWCqakpOnfujNmzZ6Nbt255nlMSkpOTS3ybRET6KCcnB+PHj0dISIhgXq1aNSgUCjg5OYmUjOj9CrWIVyaToXv37ujevTuys7Nx8eJF3Lp1S32qtJWVFerWrYvGjRvzc1IiIgnIzs7GmDFjEBYWJphXr14dCoUCtWvXFikZUeFofBaSg4MDhgwZwjtOExFJVFZWFkaNGgWFQiGY29vbIzIykmd2kiRoXGAyMzNx69Yt/Pjjj4iNjYW5uTnq1auHVq1aFXghOSIiKh2ysrIwfPhwfP/994J5jRo1oFAo4OjoKFIyIs0U6Towf/75J/7880+oVP9eA08mk8Ha2hrTpk3DhAkTSjQgERGVjMzMTAwdOhTHjh0TzGvWrAmFQgEHBweRkhFprkgFxszMDIsXL0a7du2QmZmJS5cu4ciRI/jss89w5syZPBdBIiIicWVkZGDIkCE4fvy4YF67dm0oFApUr15dpGRERVOkAjNp0iSMHj1a/eeGDRti6NChCA4OxsSJE7Fz506MGjWqxEISEVHRvX79GoMGDcKvv/4qmH/wwQdQKBSws7MTKRlR0Wl8N+ry5cujcuXK+T7m7+8Pf39/HoEhIiolXr16BX9//zzlpW7duoiMjGR5IcnSuMDUrVsXR48eLfDxZs2a4fbt28UKRURExZeeno7+/fvj999/F8xdXFygUChga2srUjKi4tO4wAwfPhx//vknJkyYgNTU1DyPR0VFwdzcvETCERFR0aSlpcHPzw8nT54UzF1dXaFQKFC1alWRkhGVDI3XwAwdOhSxsbHYvHkzjh49io4dO8LV1RWmpqb4/fff8dtvv2HIkCHayEpERIXw8uVL+Pn54fTp04J5gwYNEBYWVuAyACIpKdIi3qVLl6JXr1746quvcOLECURERAD493Rqb29vfPHFFyUakoiICiclJQV+fn44e/asYN6oUSOEhYWhUqVKIiUjKllFKjAA0LJlS7Rs2RIqlQrx8fFIS0tD9erVUbFixZLMR0REhZScnIy+ffvi/PnzgnmTJk1w5MgRyOVykZIRlbwiF5g3ZDIZatSoURJZiIioiJKSktC7d29cunRJMG/evDlCQkJYXqjM0XgRLxERlS4vXryAj49PnvLSqlUrhIaGsrxQmcQCQ0QkYYmJiejVqxeuXLkimLu7uyMkJASWlpYiJSPSLhYYIiKJevbsGby9vXH9+nXBvE2bNjh06BAsLCxESkakfSwwREQSlJCQgF69euHGjRuCefv27XHw4EFUqFBBpGREusECQ0QkMU+ePEGvXr3w999/C+YdO3ZEcHAwLyZKeoEFhohIQh49egQvLy/cunVLMO/SpQv279+P8uXLi5SMSLdYYIiIJOLBgwfw9PTMc7+57t27Y+/evTAzMxMpGZHuscAQEUnA/fv34enpiX/++Ucw79GjB4KCgmBqaipSMiJxsMAQEZVycXFx8PT0xL179wRzLy8v7N69GyYmJiIlIxIPCwwRUSn2zz//wMvLC/Hx8YK5t7c3vv32WxgbG4uUjEhcLDBERKXUnTt34OXlhQcPHgjmffr0wc6dO1GuXDmRkhGJjwWGiKgUio2NhZeXFx4+fCiY+/n54ZtvvmF5Ib3HAkNEVMrcvHkTXl5eePz4sWA+YMAAfP311zAyKvZ9eIkkjwWGiKgU+euvv+Dl5YWEhATBfNCgQfjqq69gaGgoUjKi0oUFhoiolLh27Rq8vLzw7NkzwXzo0KHYtGkTywvRf7DAEBGVAleuXIG3tzeeP38umI8cORJffvklDAz47Zrov/gVQUQkskuXLsHHxwcvXrwQzMeMGYO1a9eyvBDlg18VREQiunjxInx8fJCUlCSYjx8/HqtWrYJMJhMpGVHpxgJDRCSSc+fOwcfHBykpKYL55MmTERAQwPJC9A4sMEREIjhz5gx69+6N1NRUwfyTTz7B0qVLWV6I3kOSBSYqKgr+/v5wcXGBXC7Hvn37xI5ERFRop06dQt++ffHy5UvBfMaMGfjf//7H8kJUCJIsMOnp6XB1dcWKFSt4+3gikpTz58+jX79+SEtLE8xnz56Nzz//nOWFqJAkeTnHbt26oVu3bgCAiRMnipyGiESRnAyLs2dhdP++2EkK7cqVK1AsX4422dmCuf+AAejfqhXw668iJXs/y4cPJfVeA8ysK+XKlwecnXW+X0kWGCLSbwbXrqFCz56o+Nb6kdLOHUBkfg8cOPDvr1KsjtgBioCZdaPCF18A7u46368kP0IiIv1mvGcPZBIrL0RUsvTiCExsbKyktqtNzKw7Uswtlcy14uJgInYIIlLT1vcO53d8NKUXBeZdb0BRxcbGamW72sTMuiPF3FLKbFa+vODPua6uUNraipSmYImJibh69SpUKpVgXsfZGfYODiKlKppXr16h/Fvve2nHzLqRXbmyKN879KLAEFHZIsvNFfw5Y/Zs5Pj6ipQmf5GRkRgxYgSy3yovs2bNQuv58/FKpFxFJaWC+wYz60aaSEduJVlg0tLScPfuXQCAUqnEgwcPcOXKFVSqVAkOEvuphoiKICdH+OdSdq+g8PBwjBo1Cjlv5Vy/fj3atm0rUiqisqV0fdUX0sWLF9G+fXu0b98er1+/RkBAANq3b4/ly5eLHY2IdOGtIzAwKj0/ix05cgQjR44UlBeZTIaNGzdixIgRIiYjKltKz1e9Btq1a4fk5GSxYxCRWN4uMIaG4uR4y6FDhzBu3DgolUr1TCaTYdOmTRg8eLCIyYjKHkkegSEiPVcKj8AEBwfnKS8GBgbYunUrywuRFoj/VU9EpCHZW2tLVCIfgdm3bx8mT54sONvIwMAA27Ztg5+fn4jJiMouHoEhIukpRR8hBQUF5SkvhoaG2LFjB8sLkRaxwBCR9JSSAvPtt99i6tSpgvJiZGSEwMBA9OnTR5RMRPqCBYaIpKcUrIHZvn07Pv30U8GsXLly2LVrF3x8fHSeh0jfsMAQkfS8fR0YHR+B+frrrzFr1izBzNjYGEFBQfDy8tJpFiJ9xQJDRJLz9pV4dbmId8uWLZg7d65gZmJigr1796JHjx46y0Gk71hgiEh6RFoDs3HjRsyfP18wMzExwf79+9GtWzedZCCif/E0aiKSHhHWwKxbtw5LliwRzExNTREcHIwPP/xQ6/snIiEWGCKSHh2vgVm1alWeW5WYmZkhODgYHTp00Oq+iSh/LDBEJD06OgKjUqkQEBCAVatWCebm5uY4cOAAb8xIJCIWGCKSnDyLeLVwN2qVSoUvvvgCa9asEcwrVKiAgwcPwsPDo8T3SUSFxwJDRNKj5SMwKpUKixcvxpdffimYW1hYICQkBK1atSrR/RGR5lhgiEh6tHgWkkqlwoIFC7B582bB3NLSEqGhoWjevHmJ7YuIio4Fhoik5+1FvCV0BEalUmHevHn4+uuvBfOKFSviyJEjaNq0aYnsh4iKjwWGiKRHC0dgVCoVZs+eje3btwvmcrkcYWFhaNy4cbH3QUQlhwWGiCSnpK/Eq1QqMXPmTAQGBgrmVlZWCAsLQ8OGDYu1fSIqeSwwRCQ9JXgERqlU4tNPP8Xu3bsF8ypVqiA8PBxubm5F3jYRaQ8LDBFJTwmtgcnNzcXUqVOxb98+wdza2hoRERFwcXEpakIi0jIWGCKSnhI4ApObm4tJkyYhODhYMLexsUFERATq1q1bnIREpGUsMEQkLSpVnjUwmhaYnJwcTJgwAYcOHRLMbW1toVAo4OzsXNyURKRlLDBEJC1KpeCPKpkM0OBKvDk5ORg7dixCQ0MF82rVqkGhUMDJyalEYhKRdrHAEJG0FGP9S3Z2NkaPHo3w8HDB3N7eHgqFArVq1SqJhESkAywwRCQtRfz4KCsrCyNHjkRkZKRg7uDgAIVCgZo1a5ZQQCLSBRYYIpKWIhyByczMxLBhw/Djjz8K5o6OjlAoFKhRo0ZJJiQiHWCBKYq0NNTv0wflypUTO4lG6mdnM7OOSDG3VDLnWcD7nvUvGRkZGDp0KH766SfBvFatWlAoFLC3ty/piESkAywwRaFUwjQ+XuwUGiu5293pjhQzA9LMLcXMAKB6xxGYjIwMDB48GD///LNg7uTkBIVCgWrVqmk7HhFpCQsMEUmaytY23/nr168xcOBAnDhxQjCvU6cOIiIiYFvA64hIGlhgiEiyck1MkPHZZ3nmr169gr+/P/744w/BvF69eggPD4eNjY2uIhKRlrDAFIW5Oa4ePiy5sxbi4uKYWUekmFuKmW+9fo0P6tcXzNLS0uDv74+TJ08K5q6urggPD4e1tbUuIxKRlrDAFIWhITJr1IBSYhe8ylQqmVlHpJhbiplVsbGCP798+RL9+/fHqVOnBHM3NzeEh4ejSpUquoxHRFrEAkNEZUJqair8/Pxw5swZwbxBgwYIDw+HlZWVSMmISBsKf/1tIqJSKiUlBX369MlTXho3boyIiAiWF6IyiAWGiCQtOTkZvXv3xrlz5wTzZs2aISwsDJUqVRIpGRFpk2QLzI4dO9CwYUPY2NigQ4cOiI6OFjsSEelYSkoKfHx8cOHCBcG8RYsWCA0NhVwuFykZEWmbJAtMaGgo5s6dixkzZuCPP/5Ay5Yt4efnh3gJXlyOiIrm+fPnmDhxIi5fviyYt27dGocPH0bFihVFSkZEuiDJArNlyxYMHDgQw4YNQ926dbF69WrY2NggMDBQ7GhEpEUqlQpxcXHYt28fevbsiVu3bgke9/DwQEhICCwtLUVKSES6IrmzkLKysnDp0iVMmTJFMO/UqVOeBXxEJG0qlQp3795FVFQUTp48iejoaDx48CDf57Zr1w7BwcEwNzfXcUoiEoMsOTlZJXYITTx+/BguLi44evQo2rRpo56vXLkShw4dyrOQDwBi37pWBBGVTm+OsFy4cEH9KzEx8b2va9myJdauXQtTU1MdpCQiXXF2di7wMckdgXlDJpMJ/qxSqfLM3njXG1BUsbGxWtmuNjGz7kgxtxiZlUol/vrrL0RFRSEqKgrR0dF49uyZRtvw8vLC9u3bYWZmpqWUJUuK/28A0szNzLohVmbJFZjKlSvD0NAQT58+FcwTExN5iXCiUk6pVOLatWuCwvLixQuNtmFiYoIWLVqgTZs2cHZ2Rt++fQv84YWIyi7JFRhjY2M0btwYJ06cgK+vr3p+4sQJeHt7i5iMiN6Wk5ODq1ev4uTJk4iKisKpU6eQkpKi0TbMzMzQqlUrtGnTBm3atEGzZs1gYmIC4N+f/FheiPST5AoMAEyaNAnjxo1Ds2bN0KpVKwQGBuLJkycYMWKE2NGI9Fp2djYuXbqkPsJy+vRpvHz5UqNtVKhQQVBYmjRpAmNjYy0lJiKpkmSB6dOnD168eIHVq1cjISEBLi4uOHjwIGrUqCF2NCK9kpmZiQsXLqgLy9mzZ5Genq7RNiwtLeHu7q4uLI0aNYKRkSS/NRGRDkn2u8To0aMxevRosWMQ6ZWMjAzExMSoC0tMTAwyMjI02oZcLoeHh4e6sDRo0ACGhoZaSkxEZZVkCwwRaV96ejpiYmLUa1jOnz+PrKwsjbZRpUoVQWFxdXWFgYEkr6FJRKUICwwRqb18+RJnz55VF5YLFy4gJydHo23Y2Nioy0qbNm1Qt25dLrQlohLHAkOkx1JSUnD69GlERUXhl19+wd9//43c3FyNtlG9enVBYXFycmJhISKtY4Eh0iNJSUmIjo5Wr2G5evUqlEqlRttwcHBA27Zt0aZNG7Rt2xaOjo4sLESkcywwRGVYYmKiuqxERUXhxo0bUKk0u3tIrVq1BEdYeLYfEZUGLDBEZUhCQoKgsPz9998ab8PZ2VlQWKpVq6aFpERExcMCQyRhDx8+FBSW27dva7wNFxcXtGnTBrVr10bfvn1hY2OjhaRERCWLBYZIQu7duycoLHFxcRq9XiaTwc3NTX10xcPDA1WqVAHw72X5WV6ISCpYYIhKKZVKhbi4OPUpzVFRUYiPj9doGwYGBmjYsKG6sLi7u6NSpUpaSkxEpDssMESlhEqlwu3btwVHWB49eqTRNgwNDdG4cWP1WUKtWrVCxYoVtZSYiEg8LDBEIlGpVPj777/VZSU6OhoJCQkabaNcuXJo2rSp+ghLy5YtYWFhoaXERESlBwsMkY4olUpcv35dUFieP3+u0TZMTEzQrFkz9TVYWrRogfLly2spMRFR6cUCQ6Qlubm5uHr1qnoNy6lTp5CcnKzRNszMzNCiRQv1EZbmzZvD1NRUS4mJiKSDBYaohGRnZ+Py5cuIiorCTz/9hKtXryI1NVWjbZibm6NVq1bqwtK0aVMYGxtrKTERkXSxwBAVUVZWFi5evIioqCicPHkSZ86cQXp6ukbbsLS0ROvWrdWFpVGjRihXrpyWEhMRlR0sMESFlJGRgfPnz6vXsJw9exavX7/WaBsVK1aEh4eHeg1L/fr1YWTEL0MiIk3xOydRAV69eoWYmBh1YTl37hwyMzM12oaVlZW6sLRp0wZubm4wNDTUUmIiIv3BAkP0/6WlpeHs2bPqwnL+/HlkZ2drtA1ra2u0adMGzs7O6N27N+rVqwcDAwMtJSYi0l8sMKS3UlNTcfr0aXVhuXTpEnJycjTahp2dneDGh87OzpDJZIiNjYWzs7OWkhMREQsM6Y3k5GRER0erC8uVK1egVCo12oa9vb26rLRt2xa1atWCTCbTUmIiIioICwyVWc+fPxdclv/69etQqVQabaNmzZqCIyyOjo5aSktERJpggaEy4+nTp4IjLDdu3NB4G05OTur7CHl4eMDe3l4LSYmIqLhYYEiyHj9+LDjCcuvWLY23UbduXcERFltbWy0kJSKiksYCQ5IRHx8vKCx3797VeBuurq7q9SseHh6wtrbWQlIiItI2FhgqlVQqFe7du4eIiAjcvn0bUVFRuH//vkbbkMlkaNCggfroioeHB6ysrLSUmIiIdIkFhkoFlUqFO3fuCI6wPHz4UKNtGBoaolGjRurC0rp1a8jlci0lJiIiMbHAkChUKhVu3rypLivR0dF48uSJRtswMjJC06ZN1YWlVatWsLCw0FJiIiIqTVhgSCeUSiVu3LghKCyJiYkabcPY2BjNmjVTr2Fp0aIFzM3NtZSYiIhKMxYY0orc3Fxcu3ZNUFiSkpI02oapqSnc3NzQpUsXtG3bFs2bN4eZmZmWEhMRkZSwwFCJyMnJwZUrVxAVFYWTJ0/i1KlTSE1N1Wgb5cuXR8uWLdUfCTVr1gz379/nJfmJbG3zIwAADLFJREFUiCgPFhgqkuzsbFy8eFF9hOXMmTN4+fKlRtuoUKECWrdurS4sjRs3hrGxsZYSExFRWcICQ4WSmZmJ8+fPqwvL2bNn8erVK422YWlpCXd3d/WVbhs2bAgjI/4vSEREmuO/HpSv169fIyYmRl1Yzp07h4yMDI22UalSJXh4eKiPsNSvXx+GhoZaSkxERPqEBYYAAOnp6YiJicHJkycRFRWF8+fPIysrS6NtVKlSRXBZfhcXFxgYGGgpMRER6TPJFZhdu3YhJCQEV65cQWpqKi5fvsw7BBfBy5cvcebMGfURlgsXLiAnJ0ejbdjY2KhPaW7Tpg3q1KkDmUympcRERET/R3IF5tWrV+jUqRN69uyJzz77TOw4kpGcnIw///wTQUFBiIqKwuXLl5Gbm6vRNqpXry44wuLk5MTCQkREopBcgZk4cSIA4OLFiyInKd1evHiB6Oho9RGWq1evQqVSabSNGjVqqMtK27Zt4ejoyMJCRESlguQKDOXv2bNniI6OVq9huXHjhsbbqF27tuAIi4ODgxaSEhERFZ8sOTlZsx/LS4mLFy+iY8eOhVoDExsbq6NUupOYmIgLFy6of/3zzz8ab6NmzZpo2rQpmjZtiiZNmqBq1apaSEpERFQ077qQaak4ArNs2TKsWbPmnc9RKBRo165dkbavjSu5xsbG6vQKsQ8ePBDcqfnOnTsab8PJyQmdOnVCmzZt4OHhIYnCouv3uaRIMTcz64YUMwPSzM3MuiFW5lJRYCZMmID+/fu/8zn29vY6SlM63Lt3T/1xUFRUFO7du6fR62UyGdzc3NRnCHl4eODFixeS+8IgIiLKj158hERERERlS6k4AqOJhIQEJCQk4Pbt2wCAmzdvIiUlBQ4ODqhUqZLI6YiIiEgXJHcEJiAgACtXrswz37JlCwYNGiRCIiIiItI1yRUYIiIiIt6ohoiIiCSHBYaIiIgkhwWmmDw9PSGXywW/Ro4cKXasQlGpVOjbty/kcjnCw8PFjvNeU6dORePGjWFrawsnJyd8/PHHuHnzptixCpSUlIRZs2ahRYsWsLW1hZubG6ZPn44XL16IHe2ddu3aBS8vL9SoUQNyuVzjU/h1ZceOHWjYsCFsbGzQoUMHREdHix3pnaKiouDv7w8XFxfI5XLs27dP7EjvtG7dOnTs2BEODg5wcnLCgAEDinSFb13avn07PDw84ODgAAcHB3Tt2hXHjh0TO5ZG1q5dC7lcjlmzZokd5Z0CAgLy/NtXp04dnWZggSkBgwYNws2bN9W/1q9fL3akQtm8eTMMDQ3FjlFoTZo0wVdffYUzZ87g8OHDUKlU8PX1RXZ2ttjR8vX48WM8fvwYixcvRnR0NLZt24bo6GiMGjVK7Gjv9OaGqXPnzhU7SoFCQ0Mxd+5czJgxA3/88QdatmwJPz8/xMfHix2tQOnp6XB1dcWKFStgZmYmdpz3OnnyJEaNGoVjx44hIiICRkZG8PX1RVJSktjRClStWjUsXrwYv//+O06cOIH27dtj0KBBuHbtmtjRCiUmJga7d++Gm5ub2FEKxdnZWfBvn65/iOAi3mLy9PSEq6srVq9eLXYUjVy8eBGDBw/Gb7/9hv/X3v2GNLU+cAD/KjVBQ9SlpU4bxQSVxHKYiGC5WoWWISzbm/6jhQVlghqGpYigpWSSSSYILrqmEtPK8oVFQoYv0lAxJDUw0XChbRMR5n4vLr/u9Wo2S3d26vt5d54p+3Jg23fPeXYehUKBmpoaJCYmCh1rWXp6ehATE4POzk7R3KDv+fPnSE5OxsePH+Hu7i50nCU58r2WVCoVQkNDUVZW9m1s+/btSExMRG5uroDJbOPv74+ioiJR/XLSZDIhMDAQOp0O+/fvFzqOzeRyOXJzc3HixAmhoyxpamoKsbGxuHnzJoqKihz+c6WwsBB6vR6vX78WLANnYFZAQ0MDNm/ejKioKOTk5MBoNAodaUlGoxGnTp1CaWkpvL29hY7zU8xmM3Q6HWQyGQIDA4WOYzOj0QgXFxe4uroKHUW0Zmdn0dXVhbi4uHnjcXFxePPmjUCpfn8mkwlzc3Pw8PAQOopNLBYLGhoaYDabERkZKXScH7pw4QISExMRGxsrdBSbDQ8PIzg4GGFhYTh58iSGh4ft+vyiu5Gdo9FoNAgICMDGjRvR39+Pa9euoaenB48ePRI62nelp6dDpVJBrVYLHWXZqqqqkJubC7PZDIVCAb1eDxcXF6Fj2WRychIFBQU4evQo1qzhS+9nGQwGWCyWBeXb29sbnz9/FijV7y8rKwtbt251+DLQ29sLtVqNmZkZuLm5oba21uEvydTU1GBwcBCVlZVCR7GZUqnE7du3oVAoMDExgeLiYqjVanR0dMDLy8suGfguuojlbC55/Pjxb2OhoaGQy+VQqVTo6upCeHj4Kif9h62ZP336hJ6eHrS1tdkp2dKWu5GnRqPBrl27MDY2hlu3buHYsWN49uyZXWc0fmbzUbPZDK1WC19fX+Tl5a12xAVWe8NUITg5Oc07tlqtC8ZoZVy+fBkdHR1oaWlx+HVzCoUCr169wtTUFPR6Pc6ePYvm5maEhIQIHW1RAwMDyMvLw9OnTyGRSISOY7M9e/bMO1YqlQgPD8f9+/dx7tw5u2TgGphFGAwGGAyGJf9GJpMt+qE5NzcHb29v3L17F0lJSasVcQFbM1+6dAkPHjyAs/M/Vw8tFgucnZ0RGRmJlpaW1Y46z6+c69nZWcjlcpSUlODIkSOrFXGB5WY2mUzQaDQAgIcPH2LdunWrnvG/fuY8O+oamNnZWfj6+uLevXs4dOjQt/GMjAz09fXhyZMnAqazjZjWwGRnZ6OxsRFNTU12/5XJSkhMTERAQADKy8uFjrIonU6HtLS0ecXQYrHAyckJzs7OGB0dFc0sc0JCAoKCglBSUmKX5+MMzCKkUimkUulP/W9vby8sFgs2bNiwwqmWZmvmK1eu4Pz58/PGoqOjkZ+fj/j4+NWK912/cq6tViusVitmZ2dXONXSlpPZaDRCo9HAarWivr5ekPIC/Np5djQSiQTh4eFoa2ubV2Da2tpw8OBBAZP9fjIzM9HY2Ijm5mZRlhfg7y+V9n6PWI74+Hhs27Zt3lhaWhq2bNmC9PR00czKzMzMYGBgwK6zuCwwv2BoaAh1dXVQq9Xw8vLC+/fvkZOTg7CwMERFRQkdb1F+fn7w8/NbMC6TySCXy+0fyEaDg4PQ6/XYuXMnpFIpRkdHUVpaColEgr179wodb1FGoxFJSUkwGo3Q6XSYnp7G9PQ0AMDT09Nh35jEsGFqWloaUlNTERERgR07dqC6uhpjY2MO/UsTk8mEwcFBAH9/qI6MjODdu3fw9PREQECAwOkWysjIwF9//YXa2lp4eHhgfHwcAODm5iZYEf+Rq1evQq1Ww9/fHyaTCfX19Whvb0ddXZ3Q0b7r//dQ+TdXV1d4eno67GUvAMjJycG+ffsgk8m+rYGZnp6GVqu1WwYWmF+wdu1avHz5Enfu3IHZbIa/vz/UajWysrIc/jqx2EgkErS3t6O8vBxTU1Pw8fFBdHQ0Wltb7T7bZauuri50dnYCACIiIuY95sjrTaqrq+dtmHr48GEAjrVhalJSEr58+YLi4mKMj48jODgYdXV1Dv2LtLdv3+LAgQPfjgsLC1FYWAitVouKigoBky2uqqoKABbcXiEzMxPZ2dlCRPqh8fFxpKSk4PPnz3B3d0doaCjq6+uhUqmEjvbbGR0dxenTp2EwGLB+/XoolUq0trba9TXINTBEREQkOrwPDBEREYkOCwwRERGJDgsMERERiQ4LDBEREYkOCwwRERGJDgsMERERiQ4LDBEREYkOCwwRERGJDgsMERERiQ4LDBEREYkO90IiIlH578Z3/9bd3Y1NmzbZMQ0RCYUFhohEpbKycsFYfn4+JiYmHHaXZCJaeSwwRCQqycnJ845v3LiBkZERVFRUQCqVCpSKiOyNa2CISLRaW1tRUFCAlJQUaLVaoeMQkR05TU5OWoUOQUS0XB8+fEBcXBxCQkLQ1NSENWs4oUz0J2GBISLRMZlM2L17N75+/YoXL17Ax8dH6EhEZGf8ykJEomK1WnHmzBkMDQ3h8ePHLC9EfygWGCISlevXr6O5uRllZWVQKpVCxyEigfASEhGJRl9fH2JiYhAUFISLFy8ueDwhIQFubm4CJCMie+MMDBGJhsFgwNzcHPr7+5Gamrrg8e7ubhYYoj8EZ2CIiIhIdHgfGCIiIhIdFhgiIiISHRYYIiIiEh0WGCIiIhIdFhgiIiISHRYYIiIiEh0WGCIiIhIdFhgiIiISHRYYIiIiEh0WGCIiIhKd/wHnvlkbADDTXAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plot_activation(nn.PReLU(), name='Parametric ReLU')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([-0.7500,  0.0000,  3.0000])"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummy_z = torch.tensor([-3., 0., 3.])\n",
    "F.prelu(dummy_z, weight=torch.tensor(0.25))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([-0.7500,  0.0000,  3.0000], grad_fn=<PreluBackward>)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nn.PReLU(init=0.25)(dummy_z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Deep Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](images/classification_relu2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sets learning rate - this is \"eta\" ~ the \"n\" like Greek letter\n",
    "lr = 0.1\n",
    "\n",
    "torch.manual_seed(17)\n",
    "# Now we can create a model\n",
    "model_relu = nn.Sequential()\n",
    "model_relu.add_module('flatten', nn.Flatten())\n",
    "model_relu.add_module('hidden0', nn.Linear(25, 5, bias=False))\n",
    "model_relu.add_module('activation0', nn.ReLU())\n",
    "model_relu.add_module('hidden1', nn.Linear(5, 3, bias=False))\n",
    "model_relu.add_module('activation1', nn.ReLU())\n",
    "model_relu.add_module('output', nn.Linear(3, 1, bias=False))\n",
    "model_relu.add_module('sigmoid', nn.Sigmoid())\n",
    "\n",
    "# Defines a SGD optimizer to update the parameters\n",
    "optimizer_relu = optim.SGD(model_relu.parameters(), lr=lr)\n",
    "\n",
    "# Defines a binary cross entropy loss function\n",
    "binary_loss_fn = nn.BCELoss()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_epochs = 50\n",
    "\n",
    "sbs_relu = StepByStep(model_relu, binary_loss_fn, optimizer_relu)\n",
    "sbs_relu.set_loaders(train_loader, val_loader)\n",
    "sbs_relu.train(n_epochs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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44QXWrl2b083KtaQH2Il69uzJ4cOHad68uX3Lw5wmPRh528Prp7l0CePnn6P/9lsUiyXFY20lSxL/4YeY33yTK3/q2b5dz3ff6TlyRIuqPn3Mg06n0qSJlfbtEyfRlS2buR2EhPz85XVy/dJPeoCFM8kQiDwiLCyMmJgYvvnmGwnAwikev37K5cu4fPEF+jVrUMwpT4azVqxI/KRJWLp0AUXh778VduzQsW2bnn37dJhMaRsAXLmylfbtLbRpY8bTUyUuTiE+HmJjFeLiFGJjEzfpiItLKjOZoE4dK926mdHI35fk5y+Pk+uXfhKAhTNlZQCW0X9O1KxZMw4cOJDTzRDPMLVMGeLmziV+7FiMc+diWLUK5bEF17Xh4bi//TaWWrVI+PhjCr/8Mn37munb18z9+7B7t54dO3Ts2qUjMjL1lHrunJZz57TMnfvkGcQp2bfPxFdfxZHCyA0hhBAix+V4H83NmzcZOnQo5cuXp2jRojRs2JCDBw869RyHDh2iZ8+eVK1aFW9vb4KDg1M8LjAwkBo1alC0aFGaN2/Ojz/+6NR2COEsaqlSxP/nPzw4eZKEQYNQU1jmRnfqFO6vvYZ7585ojx8HwMsLXnvNzJIlcVy48IDt26MZNSqBihWfPG44vYKDDQwd6koqozWEEEKIHJWjATgyMpJ27dqhqirr1q3j6NGjfPbZZ6lukXf06FESEhKSlV++fJkrV66kep6YmBj8/PyYNWsWrq6uKR6zceNGxo8fz9ixYwkLC6NBgwZ0796da9eu2Y9p3Lhxirfr16+n850L4RxqyZLEz57NgxMnMPXpg5rCuAPdwYN4tGmD25tvojlzJqlcBy++aOVf/4rn+PFoTpx4wKefxvHSSxa02syPjAoJMTBggBtP2RFUCCGEyHY5OgZ42rRpHDp0iNDQ0Kceq6oqLVq0oFixYqxevdq+J/a1a9fo0KEDr776KtOmTXtqPSVKlOCzzz6jd+/eDuWtWrWiWrVqfPXVV/ayOnXq4O/vz5QpU9L8ng4cOMCSJUtkDLBwivReP83587h8+in6LVtSfF5VFMw9ehA/YQJqmTKp1hMZCXv26Pnvf3X8+qsWrRZcXVVcXR9+Tbzv5pb41cUl8WtQkIE//3QM4e3amVmxIpbncSie/PzlbXL90k/GAAtnembHAG/fvp1WrVrRv39/Dhw4QLFixejbty+DBg1KtnWfoiiEhITQsWNH+vfvz/Lly7l16xadO3emfv366QqpjzOZTJw6dYpRo0Y5lLds2ZKjR49muF4hsputUiViV6xAc+oULtOmof/hB4fnFVXFsHYt+o0bMffsScKwYdj8/JLV4+0N3bqZ6dYt5Yl2qenWzYS/vwdXriSF4NBQPb16uREcHIubW8belxBCCOFMOToE4vLlyyxdupQyZcqwYcMGhg4dyieffMKSJUtSPL5IkSJs3bqVM2fO0K9fP7p06cILL7xAQEAA2kzMtrl79y5WqzXZ0IvChQtz+/btNNfj7+9Pv3792LVrF35+fhw7dizDbRIiM2y1ahG7cSPRW7diqVcv2fOK2Yxh1So8mzTB7dVX0e3cCalsuJEeZcqofP99NOXLO44p3rtXT/fu7kRHZ/oUQgiRa61cuZJSpUql+jglX3zxBbVr13b6ucWT5WgAttls1KxZkylTplCzZk3eeusthgwZQmBgYKqv8fHxISgoiG3bthETE8OSJUvQOWkrq8d7nVVVTVb2JFu2bOHixYv89ddfnDlzhgYNGjilXUJklLVZM2J27SImOBhrKlth6vfuxb1HDzwaNsSwdCnExGTqnCVKqGzfHkOVKo4h+NAhHa+95i4bbgghcpU33ngDf3//FJ87d+4c3t7e7N27N0N1d+/enRMnTmSmeclYLBa8vb3Ztm1blp8rJdOnT6dp06ZZfp6slqMBuGjRolSuXNmhrFKlSk+cVHb37l2GDx9O69at0el0jBkzBlsme64KFiyIVqtN1tt7586dVCfkCZFnKAqWjh2JPniQ2EWLsJUuneJh2vBwXMeOxbNaNYxTp6JkYnJnsWIq27bFUL26Ywg+dkxH167uRESk/RdLIYTISn379iUsLCzFyfSrVq3C19eX5s2bZ6huV1fXbMsR2XmuZ0GOBuBGjRpx4cIFh7ILFy7g6+ub4vERERF07doVHx8fgoOD2bZtG2FhYYwePRpVzfhcPoPBQK1atZL9hrd3714aNmyY4XqFyFW0Wsw9e/LgxAliVqzA0rhxiodpIiNx+fJLPGvWxHXAALQ//ZSh0xUqpPLddzHUqeO4Ftr//qejc2d37tyRECyEyHnt2rWjSJEiyZZINZvNrF27lrfeegvNPyvsTJo0ibp161KsWDFq1KjB1KlTU1yd6qGUhiV8/vnnVKxYkZIlSzJs2DBiY2Mdnv/pp5/o2rUr5cqVo1SpUrzyyisOPbs1atQA4K233sLb29s+fCKlcwUGBlKrVi0KFy5MnTp1WLVqlf25hz3JK1eupE+fPhQvXpxatWqxfv36tH7rUhQREcHgwYMpXbo0Pj4+vPrqq5w7d87+fGRkJIMGDbIvf1urVi0CAgIc2lynTh2KFCmCn58f3bp1y3RHZ0pyNAAPHz6c48ePM2fOHC5dusTmzZsJCAhg4MCByY5VVZUePXpQoEABgoODMRqNlClThq1bt7J7926mT5+e6nmio6M5ffo0p0+fxmazcf36dU6fPu2wxNmIESNYs2YNK1eu5Ny5c4wbN46bN2/Sv3//LHnvQuQYnQ6Lvz8xO3YQvXcvph49UFMYRqRYrRg2bsSjdWvcO3VC88gHWFrlz6+yaVMMDRs6huBff9XSsaM7N29KCBbieZDP2ztbb+mh0+no1asXa9ascQhaO3bs4O7duw6rRnl6erJgwQKOHj3K7NmzWbduHV988UWazxUSEsKsWbOYNGkS+/bto0yZMixatMjhmOjoaHr16sWOHTvsc4pef/11IiMjAfjhn8nN8+fP59y5c+zevTvFc23evJkJEyYwcuRIDh8+zMCBA3nvvffYtWuXw3H//ve/6dKlCwcPHqRz584MHz6cP//8M83v6XFDhgzh559/5ptvvmHXrl3o9Xq6detGfHw8kLgC2Pnz5wkJCeH48eN89dVXFC1aFEgM/+PHj+ejjz7ip59+Yt26dbz88ssZbsuT5GgArlOnDsHBwWzatInGjRvzr3/9i48++ijFAKwoChMnTuSbb75xWBKjfPnybNmyhV69eqV6nv/97380a9aMZs2aERcXx8yZM2nWrBkzZsywH/Paa68xc+ZMZs+ezUsvvcSRI0dYt26dDCgXzzRr7drEBQTw4JdfiB87Flv+/Ckepzt4EI+mTTHOmAH/fIilVb58sGFDDE2bOobgc+e0dOjgzqVLOb4fjxDiOdenTx+uX7/Ovn377GWrV6+mZcuWlCxZ0l42btw4GjZsSOnSpWnXrh3vvfceGzZsSPN5Fi5cyFtvvcXbb79NhQoVGDdunL1H96EWLVrwxhtvULlyZSpXrsycOXPQaDTs2bMHgEKFCgGQL18+ihYtSsGCBVM819dff82bb77JwIEDqVChAsOHD6dbt258+eWXDsf16tWL7t27U65cOSZPngzAkSNH0vyeHnXu3Dl27tzJV199RZMmTahevToBAQFERkbav0/Xrl2jZs2a1KlTh1KlStGsWTP7GOxr167h4eFB+/btKVWqFNWrV2fkyJH2HnhnyvH/edq1a8ehQ4e4desWJ06cYOjQoalOPGvRogVuKayjVKlSJSpUqJDqOV566SUiIyOT3RYuXOhw3MCBA/nll1+4ffs2+/fv58UXX8zcmxMij1B9fEiYPJkHv/1G7JdfYn1sbD4krhzh8tlneLz0Etp07tbo4QHr1sXQsqXjsmqXLmlp0sSDzz4z8oS/IgohRJYqX748TZo0YfXq1QD89ddf7Nmzhz59+jgct3HjRtq1a0elSpUoUaIEkydPTtdmWOfPn6d+/foOZY9PmL99+zajR4+mbt26lCpVipIlS3Lv3r10b7p1/vz5ZMM4GzVq5DAcAaB69er2+waDgYIFC/L333+n61wPnTt3Dp1OR71HVh/y9vamSpUq9vO+8847hISE0LRpUyZPnsyhQ4fsx7Zq1QofHx9q1qzJ4MGDWbduHdFZtHxQjgdgIUQu4uaGuV8/oo8cIWbDBizNmiU7RBsejkenTriOHIkSEZGeqlmzJpb27R1DcHy8wowZLjRp4sG+fRlfzlAIITKjb9++bN++nYiICNasWUP+/Pnp0KGD/fnDhw8zaNAg2rRpw7fffktYWBgfffQRJidvdzl48GBOnz7NzJkzCQ0N5cCBA/j4+GToPCl1KD5e9vhKWoqiZHjM7ZPmYz08b/v27fnll18YMWIEt2/fpnv37rz77rsAeHl5ceDAAZYuXUrx4sWZO3cuDRs25NatWxlqz5NIABZCJKcoWFq1ImbLFmKDgrAVKZLsEMPq1XjUr48+JATSOAnVxQVWrozl1VeTf5BfvKila1cP3nnHVcYGC/GMiYqMzNZbRvj7+2M0Glm7di2rV6+mZ8+e9l1nAY4ePYqvry/vv/8+derUoXz58ly9ejVd56hUqRI/PTax+Pjx4w6Pjxw5wpAhQ2jbti1Vq1bFzc3NIQBqtVq0Wi1Wq+MqOymd6/GhDEeOHEm2+pYzValSBYvF4vAeIyMjOXv2rMN5CxUqRK9evVi8eDFffvklq1evxmxO7BzR6XS0aNGCqVOnsmfPHqKioti5c6fT25qjO8EJIXI5RcH82muYW7bEZepUjMuXOzytuXMHt0GDMH/zDXGff/7E7ZUfMhggKCiOdu0sTJrkwp07jr+Hb9hgYNcuPRMnxjNwoIlM7HEjhBBp5urqSvfu3Zk1axaRkZHJhj+UL1+e69evs379eurWrcuuXbvYtGlTus4xdOhQRo0aRc2aNWnSpAmbNm3i559/to/rfXietWvXUrt2baKjo5k8eTJGo9H+vKIolCxZkrCwMBo1aoTRaMQ7hYl/7777LgMHDqRGjRq0aNGC0NBQNmzYwLfffpvO70xy8fHxnD592qHM3d2dypUr065dO0aPHs0XX3yBp6cn06ZNw9vbm9deew1IXEe4du3aVKlSBbPZzLZt2yhfvjx6vZ7t27dz7do1mjRpgre3N7t37yY2NjZLQrv0AAshns7bm/gvvyR6x44Uxwfrf/gBz8aNMcydC+anb5+sKNCzp5mffnrAgAEJKIpjD/L9+wrjxrnSsqUHJ09KAhZCZI8+ffoQGRlJw4YNk4WuhyskjBs3jpdeeomDBw8yYcKEdNXfo0cP3n//faZNm0bz5s0JDw9nyJAhDscsWLCAqKgomjVrxsCBA+nfvz8lSpRwOObTTz9l7969VKtWLdVVEvz9/Zk5cyZff/01jRo1IjAwkC+++II2bdqkq80puXDhgn1xgYe3h+9j0aJF1KhRgzfeeIM2bdpgMpnYsGGDfQEDvV7PtGnTaNq0Ke3btychIYE1a9YAieOFv/vuO/z9/WnQoAEBAQHMnz8/SzYWUyIjIzO+gK7I9cLDw6lYsWJON0NkUK68fgkJGOfOxThnDkoKY9Ks1asTu3w5tidMTH3cTz9p+b//c+X06eRhV1FUBgwwMXlyPOlc3SjH5crrJ9JMrl/6RUVFkS9fvpxuBpDYS/noqlEi70nLNczovznpARZCpI/RSMKHHxL9449YUtgOU/vrr3i0aoUuHVuH1qtn5Ycfopk1Kw5PT8ffyVVVYelSI/XqeTJqlCvLlhk4dUqDk+edCCGEeI5IABZCZIitQgVivvuO2Hnzkq0frERF4fb66xgWLUrzBDmdDoYONXHs2ANeey15ur1zR8OqVQbGjHGlRQtPSpb0omVLd95/34XVq/WcOaPhKXNChBBCCEACsBAiMxQF81tvEX38OKZXX3V8ymrFdfx4XEePJj3dtT4+KkFBcWzaFEP58qknWpNJ4eRJHYGBRkaOdKNJE098fb145RV3Jk504dw5+XgTQgiRMvkfQgiRaWqhQsQFBRE3bRrqY2tMGlauxN3fH+XOnXTV+fLLFg4dimbChHhcXdPWixwbq3D4sI758420bu3BlSuynJoQQu+HxPIAACAASURBVIjkJAALIZxDUTC9+y6x336L6unp8JTu8GE8Xn4Zza+/pqtKFxcYNy6Bc+fus2lTDJMnx9Opk5kSJZ6+SPuDBwrz5hmfepwQQojnjwRgIYRTWdq1I3rXLqxlyzqUa65dw6NdO3TffZfuOr28EnuEx45NYPXqWH777QHnzt3n229jGDcunrZtzRQqlDwUBwcbiIiQXmAhstOTdgMTwpky829NArAQwulsVaoQs2dPsq2UlZgY3Pv0wTh7dponx6WmaFGV9u0tTJiQwLp1sYSHP+CXX+5TvHhSEI6NVVi2zJCp8wgh0s7d3Z3IyEgJwSLLqapKZGQk7u7uGXq97AQnhMgSaoECxGzYgMtHH2FcssThOZdPP0Xz++/EzZsHbm5OOZ+igK+vypAhCUyZ4movDwgwMHJkAgbJwUJkOZ1Oh6enJ/fv38/ppnD//n28vLxyuhkiE552DT09PdHpMhZlJQALIbKOXk/87NnY/Pxw+eADFIvF/pRh40Y0ly4R+803qD4+Tjvl22+b+OwzF2JiEoc+3LypYeNGPT17Pn2HOiFE5ul0ulyxGcbt27fx9fXN6WaITMjKayhDIIQQWc7Uvz8xmzZhK1DAoVx36hRuvXqlafvktPL2ht69HZddmz/fmNkRF0IIIZ4hEoCFENnC+tJLRP/wA9aqVR3KdadOJY4JdqJhw0woSlLi/eUXLQcOJN9mWQghxPNJArAQItuoZcoQHRqK+eWXHcqN//kP2hMnnHaesmVtdOxocSibP1+WRBNCCJFIArAQInt5eRG3dCm2okXtRYrViuuQIRAb67TTjBiR4PA4NFRPeLh85AkhhJAALITIAWqBAsR9/bVDmfbCBVymTHHaORo1slKnjmMv8IIFshSEEEIICcBCiBxiaduWhH79HMqMS5ag27vXKfUrCowY4TgZ7ptvDNy9KxtjCCHE804CsBAix8RPn55sxzjXESMgMtIp9fv7mylZMmljjPh4haAg6QUWQojnnQRgIUTO8fAgbuFCVE3SR5Hmxg1cP/jAKdXrdDBkiONY4CVLDCQkpPICIYQQzwUJwEKIHGVt1IiE0aMdygwhIeg3bXJK/X37mvDwSFoS7fZtDevX651StxBCiLxJArAQIsclTJiAtXp1hzKXMWNQ/vor03Xnywd9+sjGGEIIIZJIABZC5DyDgdjFi1ENSeNzNZGRuI4ciTOS6pAhCWg0SfWcOaNl3z7ZCV4IIZ5XEoCFELmCrVo14idNcijT79mDYdmyTNddpoxK586Pb4whk+GEEOJ5JQFYCJFrmEaMwNK4sUOZy6RJaC5ezHTdj2+MsXu3nt9/l49AIYR4HsmnvxAi99BqiV24ENXDw16kxMbiOnQoWCxPeOHTNWhgpUEDxzoWLpTtkYUQ4nkkAVgIkauoZcoQN2OGQ5nu+HGMX36Z6bof7wVeu1bP33/LxhhCCPG8kQAshMh1zH36YG7f3qHMOGsWmlOnMlVvx44WSpVK2hgjIUFh6VIZCyyEEM8bCcBCiNxHUYj76itsBQsmFVkseLRpg+s776D98ccMrQ6h08HQoY69wIGBBuLjM91iIYQQeYgEYCFErqQWKULcY8MeFLMZw4YNeHTogEeTJhgCA+H+/XTV+9ZbJry8ksLznTsa1q1LvjGG2QzXryscP65lyxYdixcbmDHDyObNOllDWAgh8jhZCFMIkWtZOncmoV8/jMuXJ3tO+/vvuL7/Pi5Tp2Lq0QPTgAHYHttMIyVeXom7w82blzQBbs4cF/73Py03bmi4eVPDX38p/P23gqqmPD540qR43n9f9lMWQoi8SnqAhRC5WvznnxM3Zw7W8uVTfF6JjsYYFIRn06a4t2+Pft06SHhyOB08OAGtNqkb9+pVDcuWGQkN1fPzz1pu39akGn4BvvzSyIMHGXs/Qgghcp4EYCFE7qbRYBo4kOjjx4nevBlz586oWm2Kh+qOHMFt8GA8/fwwLFmSapWlSqn4+5sz3KToaIUNG5IPmxBCCJE3SAAWQuQNGg3WFi2IXbWKB7/8Qvy4cdiKFUv50Lt3cf3gA7QHD6Za3dixCbi6Pnkwb+HCNl54wUq7duZkawgHBRllLLAQQuRRMgZYCJHnqMWLkzBhAgnvv4/u++8xLl2KLiws2XHGefOIbdo0xTqqVbOxdWsM332nR1GgWDEbxYvb8PFRKVbMRrFiKoZHVki7elWhZk1P+9CI06e1nDyppW5da5a8RyGEEFlHArAQIu/S67H4+2Px90dz/jyGgACMgYH2p3WhoWguXsSWyvjh+vWt1K+ftgBbqpRK27YWQkOThj4EBRmoWzcuc+9BCCFEtpMhEEKIZ4KtUiXiZ8/GUru2vUxRVQyLFjntHP37mxweb9yoJzLSadULIYTIJhKAhRDPDkXBNGyYQ5FhzRqclVLbtLFQsmTSTnJxcQpr18pOckIIkddIABZCPFPMXbs6TI5TYmIwrFrllLq1Wnj7bcde4GXLDDIZTggh8hgJwEKIZ4vBgGngQIciY0AAWCypvCB9+vQxOawhfPaslsOHU16WTQghRO4kAVgI8cwx9euH6uJif6y5dg3d9u1OqbtYMZWOHR3D9LJlMgxCCCHyEgnAQohnjlqoEOYePRzKjE6cDDdggONOc1u26LlzJ/Wd44QQQuQuEoCFEM+khKFDHR7rDh9G+7//OaXuZs2slCuXtHyayaSwZo3sDCeEEHmFBGAhxDPJ5ueHuUULhzLDwoVOqVujSb4k2rJlBmy2VF4ghBAiV5EALIR4Zj2+JJp+0yaUv/5ySt1vvmnGYEiaDPfHH1r275e9hYQQIi+QACyEeGZZ2rTBWqGC/bFiNmNYutQpdRcsqNK1q9mhLChIJsMJIUReIAFYCPHs0mgwPTYW2LBsGcQ5Z/vix4dBfP+9jr/+kslwQgiR20kAdqKePXtSunRp+vbtm9NNEUL8w9SzJ2q+fPbHmrt30YeEOKXuRo2sVK2aNBnOalVYtUp6gYUQIreTAOxEw4cPZ5ETl1oSQjiBhwemt992KDIuWoQztm9TlOS9wCtWGJy154YQQogsIgHYiZo1a4aHh0dON0MI8ZiEQYNQtUm7tWnPnEEbFuaUut94w4SbW1KY/vNPDbt2yWQ4IYTIzXJNAP7Pf/6Dt7c3H3zwgdPrPnToED179qRq1ap4e3sTHByc4nGBgYHUqFGDokWL0rx5c3788Uent0UIkf1UX1/MnTs7lBkXLHBK3fnyQbdujpPhZGc4IYTI3ZwWgG/evMnZs2cz9Nrjx4+zYsUKqlWr9sTjjh49SkJCQrLyy5cvc+XKlVRfFxMTg5+fH7NmzcLV1TXFYzZu3Mj48eMZO3YsYWFhNGjQgO7du3Pt2jX7MY0bN07xdv369TS+UyFETkm2JFpoKJoLF5xS94ABjsMgdu3SceWKTIYTQojcKt0BeNmyZQwZMsShbOzYsfj5+dGkSRNeeukl7t69m+b6oqKiGDRoEF9//TXe3t6pHqeqKh9++CF9+/bFbE7qbbl27RqdO3dm6ROWNmrbti0ff/wx/v7+aDQpv+X58+fz5ptv8vbbb1O5cmVmz55N0aJFCQoKsh9z+PDhFG8lS5ZM8/sVQuQMa4MGWOrUcSgzLF7slLpr17ZSs2bSZDhVlclwQgiRm6U7AK9YsQJPT0/747CwMIKCgnj99df5+OOP+eOPP5gzZ06a63vvvffw9/enefPmTzxOURRCQkK4dOkS/fv3x2Kx8Oeff9K5c2fq16/PlClT0vtW7EwmE6dOnaJly5YO5S1btuTo0aMZrlcIkYsoSrJeYENwMERGOqX6AQMc/zq1cqUBi0V6gYUQIjdKdwC+cuUKVapUsT/evHkzJUqUYNGiRbz33nsMGjSIHTt2pKmuFStWcOnSJSZOnJim44sUKcLWrVs5c+YM/fr1o0uXLrzwwgsEBASgfWSCS3rdvXsXq9VK4cKFHcoLFy7M7du301yPv78//fr1Y9euXfj5+XHs2LEMt0kI4Xxmf39sPj72x0psLIZVq5xSd7duZjw9kybD3b6tYf/+1P+qJYQQIuekOwCbTCb0er398d69e2ndurV9aEG5cuW4efPmU+sJDw9n2rRpLFmyBIMh7X8q9PHxISgoiG3bthETE8OSJUvQ6Zwz41pRHHtrVFVNVvYkW7Zs4eLFi/z111+cOXOGBg0aOKVdQggnMRgwDRzoUGRcvBhnrFvm4ZG4IsSjNmwonMrRQgghclK6A3Dp0qXZt28fACdPnuTy5csOQwdu377tMEQiNceOHePu3bs0btyYggULUrBgQQ4dOkRgYCAFCxZMcbIbJPbWDh8+nNatW6PT6RgzZgw2my29b8NBwYIF0Wq1yXp779y5k6xXWAiRt5n69UN1cbE/1ly/jm77dqfU3a+fYwA+ftyLCxdyzWI7Qggh/pHuT+YBAwawefNmmjRpwmuvvUaJEiVo06aN/fkjR444DJFITceOHfnxxx85cOCA/Va7dm26devGgQMHUuwVjoiIoGvXrvj4+BAcHMy2bdsICwtj9OjRqJlY1N5gMFCrVi327t3rUL53714aNmyY4XqFELmPWrAg5jfecCgzLlzolLqrV7fRsKFjb/Ly5TIZTgghcpt0B+CBAwcyd+5cypUrxyuvvMKGDRvsS4tFRETw999/071796fW4+3tjZ+fn8PNzc2N/Pnz4+fnl+JwhB49elCgQAGCg4MxGo2UKVOGrVu3snv3bqZPn57quaKjozl9+jSnT5/GZrNx/fp1Tp8+7bDE2YgRI1izZg0rV67k3LlzjBs3jps3b9K/f//0fouEELlcwtChDo91R46gPXHCKXU/vjPcypUG/vxTJsMJIURuokRGRmZ+P1An6dixI35+fsyePTvF5/ft20eDBg1wc3NzKD9//jwajYYKFSqk+LoDBw7Q+bFF8AF69erFwkd6fgIDA5k7dy63bt2iatWqzJgxgxdffDET7yjnhYeHU7FixZxuhsgguX5Zx+2119D/8IP9sbVGDaJ374Z0zElISVwc+Pl5EhGR1L/Qpo2ZdetiSceUApELyM9f3ibXL+/LymvolACckJDAd999R2RkJK+88golSpRwRtuEE8gHQN4m1y/r6Pbswb1bN4ey+DFjSMjEkooPLV5sYNw4x0135s+PpXdvcyqvELmR/PzlbXL98r6svIbpHgLx/vvv07RpU/tji8VCu3btGDx4MB988AGNGjXit99+c2ojhRDC2SwtW2Lq2tWhzPjll2gPHsx03YMGmWjc2HEs8IQJrty4IV3AQgiRG6Q7AO/fv5927drZH2/atImff/6ZOXPmsGvXLgoWLJjqEAYhhMg1FIX4L77AVrx4UpGq4jZ0aKY3x9BoYP78OIzGpN3h7t9XGDPGlUzM1xVCCOEk6Q7Af/31F6VLl7Y//v7776levToDBgygXr16DBgwQDaAEELkCWr+/MQ+tgKE5vp1XD/4INN1lytnY8SIPx3KQkP1fPONPpVXCCGEyC7pDsA6nY64uDggcWWGsLAwWrVqZX/e29ube/fuOa+FQgiRhazNm5MwcqRDmSEkBH1ISKbrfuON28mGQowfL0MhhBAip6U7APv5+bFu3ToiIyNZvXo1ERERtG7d2v781atXKVSokFMbKYQQWSl+8mSsfn4OZa5jx6JcvZqpejUamDcvDlfXpHEPMhRCCCFyXroD8Lhx4/jtt98oV64co0ePpmHDhg6T4kJDQ6lTp45TGymEEFnKaCQ2MBDVaLQXKffv4zZsGFitT3jh05Uvb2Py5HiHstBQPWvXylAIIYTIKekOwM2bN2f//v3MmDGDr7/+mk2bNtmfi4iIoGnTpgwePNipjRRCiKxm8/MjfupUhzLdoUMY5s3LdN1Dhpho1MhxKMS4ca7cvClDIYQQIifoMvKiypUrU7ly5WTl+fPnZ+bMmZlulBBC5ATTkCHodu5E/8i26C7Tp2Np3hxbrVoZrlerTRwK0bSpB/HxiaE3Kkrhvfdc+eYb2SBDCCGyW4YCMMAff/zBzp07ufrPGLlSpUrRtm1bypYt67TGCSFEttJoiFuwAG2TJmgiIgBQzGbcBg8met8+eGwXyvSoUMHGpEnxTJqUtEHGf/+rZ906PW+8IRtkCCFEdkr3EAiAiRMnUq9ePcaPH8+CBQtYsGAB48ePp169ekycONHZbRRCiGyj+vgQN3euQ5n2/HlcnLBD3LBhJho2fHwohIsMhRBCiGyW7gA8f/58FixYQIcOHdi5cydXrlzhypUr7Ny5k44dO7Jw4UIWLFiQFW0VQohsYenSBVPv3g5lxiVL0O3cmal6Hw6FcHFJWgIiMlIjq0IIIUQ2S3cAXrlyJW3btmXVqlXUr18fLy8vvLy8qF+/PitXrqR169YsX748C5oqhBDZJ27WLKxlyjiUuY4ciXLnTqbqrVjRxsSJjqtC7NihJyREVoUQQojsku4AfPnyZdq2bZvq823btuXKlSuZapQQQuQ4T0/iAgJQtVp7keb2bVxHjSKz3bXDh5uoX99xKMSHH7pw65YMhRBCiOyQ7gCcP39+wsPDU33+woUL5M+fP1ONEkKI3MDaoAEJ77/vUKbfsQP9qlWZqlerhfnz4zAaHYdCjB7tis2WqaqFEEKkQboDcIcOHVi6dCnBwcGoj/SCqKrKmjVrCAoKomPHjk5tpBBC5JSEDz7AUq+eQ5nLtGnw4EGm6q1UKflQiP/+V8+770oIFkKIrJbuAPzxxx9TuXJlRo0aRaVKlWjfvj3t27encuXKjBgxgsqVKzN58uSsaKsQQmQ/nS5xKMQjS6Bp7tzB6IQNMkaMSD4UYvVqg4RgIYTIYukOwN7e3vzwww/MmjWLmjVrcu/ePe7du0eNGjX47LPPWLNmDdevX8+KtgohRI6wlStHwogRDmXG+fNR/v47U/VqtbBkSSw+Po5pV0KwEEJkrQytA2wwGBg8eDDr16/n2LFjHDt2jPXr1zNo0CDWrl1Ls2bNnN1OIYTIUQmjRmErWND+WImOxjh7dqbrLVNG5bvvYiQECyFENspQABZCiOeOlxcJY8c6FBmWLUO5fDnTVVeoYEs1BMvEOCGEcD4JwEIIkUamd97B5utrf6yYzbh8+qlT6k4tBK9aJSFYCCGcTQKwEEKkldFI/GPbvRtCQtCcPu2U6h+G4GLFJAQLIURWkgAshBDpYO7eHaufn0OZy7RpTqu/QgUb27alHILfe09CsBBCOIMuLQedOHEizRXeuHEjw40RQohcT6slfsoU3N94w16k370bbVgYVidNAH4Ygjt1cufmzaR+ipUrDQB8+WUcGum+EEKIDEtTAG7dujWKkrYtOlVVTfOxQgiRF1natsXSpAm6H3+0l7l88gkxu3eDkz7/JAQLIUTWSVMAnj9/fla3Qwgh8g5FIf6TT/Bo08ZepDtxAt3WrVj8/Z12modjgjt3Th6CTSaYOTOe/PnVJ9QghBAiJWkKwG+++WZWt0MIIfIUa/36mDt2RL99u73MZfp0ojt2BF2aPlrTpGLFlEPwt98a+P57PSNHJjBsWAKenk47pRBCPPPkD2hCCJFB8R9/jPrIOARteDj64GCnn+dhCH58Ytz9+wozZrhQs6YnX39tIC7O6acWQohnkgRgIYTIIFvlyph793Yoc5k5E2JjnX6uhyG4VKnky0Dcu6dh8mRXatf2JDAwcXiEEEKI1EkAFkKITIgfPx7VxcX+WHPzJsbFi7PkXBUr2jhy5AGffBJH/vzJg/DNmxref9+VevU8CQ7WY7FkSTOEECLPkwAshBCZoJYogWnwYIcy4xdfoEREZMn53Nxg9GgTp049YNy4eDw9k0+Cu3pVw4gRbjRu7MGmTXpZO1gIIR4jAVgIITIpYcwY1Hz57I+V+/cxfvFFlp4zXz6YMCGBU6ce8O67Cbi6Jg/C4eFa+vd3o0ULD377TT7uhRDiIflEdKKePXtSunRp+vbtm9NNEUJkIzV/fuLHjHEoMyxejP7mzSw/d8GCKtOmxfO//z1g0KAE9PrkQfj0aS0tW3oQGGhAlVXThBBCArAzDR8+nEWLFuV0M4QQOcA0eDA2Hx/7YyUhgeJLlmTb+YsVU5k9O56ffnpA794mNBrHpJuQoPD++6707u3GvXuyWZEQ4vkmAdiJmjVrhoeHR043QwiRE9zciB8/3qGo0LZtaM6ezdZmlC6tMn9+HEePRuPvb072/Pff63npJQ8OHdJma7ueJCoKfvtNw86dOoKCDHz+uZEjR3JP+4QQz54cDcBLliyhSZMm+Pr64uvrS5s2bQgNDXX6eQ4dOkTPnj2pWrUq3t7eBKeyTmdgYCA1atSgaNGiNG/enB8f2eZUCCGexty7N9aKFe2PFZsNl3/9K0faUrGijRUrYgkIiE02Ue7PPzV07uzOjBnGbFkpIjISwsK0rFmjZ/ZsI6NHu/L66240auSBr68XpUvn48UXPenRw53/+z9Xpk1zoX17DxYtMmR944QQzyXnbVeUAcWLF+eTTz6hfPny2Gw2vvnmG3r37s2+ffuoXr16suOPHj1KrVq1MBqNDuWXL19GURRKly6d4nliYmLw8/OjV69eDB06NMVjNm7cyPjx4/nPf/5Do0aNCAwMpHv37hw5cgRfX18AGjdunOJrQ0JCKFmyZHreuhDiWaTTET95Mu6PzAPQb9+O9uRJrHXq5EiTevQwU7++lXfeceXkyaSPfJtN4bPPXDhwQEdAQCy+vs4dHHz7tsL27Xq++05HWJgOiyX9wy7Gj3dFq4VBg2RhYyGyQ1iYlvfecyU2VqFePSsvvmihaVML1arZ0DxjYwaUyMjIXDUlokyZMkyZMoX+/fs7lKuqSosWLShWrBirV69Gr9cDcO3aNTp06MCrr77KtGnTnlp/iRIl+Oyzz+j92OL1rVq1olq1anz11Vf2sjp16uDv78+UKVPS3P4DBw6wZMkSVq5cmebXZKXw8HAqPtIjJfIWuX55kKri3ro1uhMn7EXmVq2I3bAhBxsFJhN8+qkLc+cakz2XL5/K11/H0qVL5rqDr19X+O47PVu36jlyRIuqOmes8eefxzFgQPaHYPn5y9vk+qVPfDzUqOHJ7dvJk27+/DaaNEkKxNWrZ08gzsprmGvyvNVqZcOGDcTExNCgQYNkzyuKQkhICJcuXaJ///5YLBb+/PNPOnfuTP369dMVUh9nMpk4deoULVu2dChv2bIlR48ezXC9QojnkKKQMGmSQ5F+zx60hw/nUIMSGQzwySfxbNwYQ5EijgsDR0Up9O3rzv/9n0u6t1O+eFHDl18aaNnSnerVvZgwwZXDh3XpCr9Go0q5clZeeslCjx4mjEbHfpn/+z9Xli/Xp69h4okSEpDJkMLB+vX6FMMvQESEhu3b9Xz0kSvNmnlSrpwnvXq5MX++gV9+0eTJ1WVydAgEwG+//Ubbtm2Jj4/H3d2d1atXU61atRSPLVKkCFu3bqVjx47069eP33//nRdeeIGAgAC02oxPmLh79y5Wq5XChQs7lBcuXJjbt2+nuR5/f39+/fVXYmNj8fPzY/ny5SmGeSHEs83SogWWJk3QPTKPwGX6dGK2bQMlZ0NHy5YWDh2KZtgwV3bvdgyVQUFG/vtfPT4+NvR60OlAr1fR60GrBb0+8bFOl/j41CktZ86k7bO3YkUr1atbKVFCpWRJGyVK2PD1tVGihEqhQqrDt6VHDzNvvumGyZRU+N57bmg0sfTtm3xiX1qoKly6pMFigcqVn6+dQWy2xF9UTpzQcuKElpMntfzyixaTSaF1azMBAXEUKJAHE4xwGlWFBQuS/3UoNZGRGnbs0LBjR+JnSJcuZpYtiyUTUSzb5XgArlixIgcOHCAqKoqtW7cybNgwtm3bhp+fX4rH+/j4EBQUZB8OsWTJEnQ657wN5bH/mFRVTVb2JFu2bHFKO4QQeZyiED9xIh4dO9qLdIcOoQ0Lw9q8eQ42LFHhwirr1sWyYIGBTz5xwWxO+py7cUPDjRvO+eNgzZpWOnc207mzOV2hs3VrC6tXx/LWW44hePToxDHBvXunLwSfOqVhyhRX9u9P/L/ilVfMzJsXR8GCz2bou3VLsQfdxK86oqJS/r9s9249bdtqCAmJpWzZ5+sXg7xKVWHzZj0bNuh58UULQ4eaMv17dViY4y+zGo3KhAkJnDyp5ccfU//389DWrXqWLjUweHDeGa+f4wHYYDBQrlw5AGrXrs3JkydZsGAB8+bNS/H4u3fvMnz4cFq3bs3Zs2cZM2YM8+fPR5OJwSgFCxZEq9Um6+29c+dOsl5hIYRIC+uLLxLVsCH5HhlG5TJ9OjHNmuV4LzCARgMjR5p48cXECXKXLjmn66ZhQwudOiWG3jJlMh4w27a1sHJlLH36uNkDuqoqjBzpikYDvXo9PQRfvqzw6acuhIQ4riaxY4eel17SEhAQS9Om1gy3MTe5e1fh00+N7Nyp5/r19P1/eOGCljZt3Pn221jq1Xs2vh/PsnnzDEye7ArAtm16FAWGDs1c8Hy897djRwsffJAAgNUKv/6q4dAhHQcP6jh0KOVAPG2aC6+8Ynb6hNqskmvGAD9ks9kwmVK+kBEREXTt2hUfHx+Cg4PZtm0bYWFhjB49GjUTA1AMBgO1atVi7969DuV79+6lYcOGGa5XCPF8u/HYqjO648fR7dqVQ61JWe3aVvbvj6Z3bxNabfo/R7ValWbNLMyZE8fvv98nNDSGUaNMmQq/D7Vvb2HFiliH3e1UVWH4cFfWrUt9TPC9ewoTJ7rQoIFnsvD70I0bGrp0yb6l4LLahx+6EBRkTHf4fejOncSl8bZty/F+sRxhztjImmy3fr3eHn4f+ve/jURFZbzOCxc0hIY6/jwNH55gv6/VQs2aNoYPN7FmTSyXLt0nLOwBM2bE4eWV9LMZHa0wdqxrnhkPnKP/0qdOnUrbtm0pUaIE0dHRrF+/limjrAAAIABJREFUnoMHD7Ju3bpkx6qqSo8ePShQoADBwcEYjUbKlCnD1q1b6dSpE9OnT2fy5Mkpnic6OppLly4BiQH7+vXrnD59mvz589uXOBsxYgRDhgyhbt26NGzYkKCgIG7evJlsNQohhEirmOrVMbdvj/6//7WXuUyfTnSbNrmiF/ghT0+YPz+OadPiuXo1cZys2Zx4s1gU++PEr0mPPT2hWTNLlg4l6NDBwrJlsfTr52ZfSk1VFYYOTewJfv31pOQSFwcBAQb+8x8X7t9/+vf30aXgliyJpWTJPPI/92MePEj8E/STeHmp1K1roW5dK3XqWHnhBSv/+pcL69Yl/YIQF6fQp48bM2fGZ7pHMa+w2WDcOBdWrDBQoYKNmTPjaN48d/aC79+vZdgw12TlEREa5s0zMnFiQgqverrFix1/SaxVy0KjRql/D7RaqFHDRo0aJlxcEiepPrRzp56NG/V065b7f6PI0WXQhg0bxoEDB7h9+zZeXl5Uq1aNd999l1atWqV4/L59+2jQoAFubm4O5efPn0ej0VChQoUUX3fgwAE6d+6crLxXr14sXLjQ/jgwMJC5c+dy69YtqlatyowZM3jxxRcz8Q5zniwDk7fJ9cvbwsPDqRwXh2ezZg7lMStXYunSJYdalTdt2aJjwAA3rNakYKvRqAQGxuHvb2btWj0zZrik2gNavbqVKVPi+fFHLV9+aUy2SoW3t4158+Lo1CmpOziv/Pxt3aqjb193+2OdTqVmzcSgW7du4q18+eTLVqkqfPqpkTlzXJLVOXx4AtOnx+fptV/Tcv3WrNEzfLhjphg+PIGPP47HJfm3Jcf88ouGDh08ePAg5V/s3N1VTp16QOHC6Yt0kZHg5+dFbGxSvQEBsfTokbYAa7NBx47uHD6c1J9aqJCNY8einTKxMit/BnPdOsDCufLKB7hImVy/vO3h9XN7+230j0yStVatSvTBg+SpKdO5wObNOt55xzEEa7UqFSrYOHcu5e9lyZI2Jk6Mp0cPs/3bvXevjiFDXFNc8mngwMTg5+KSd37+RoxwJTg4qRdv+PAEZsyIT/PrV67UM2aMq8P3FaBzZzMBAbG4Ju90zBOedv2io6FePU9u3kz+76BqVSuLF8dSo0bOTwy8elWhbVuPZO308FCJjk66ZkOHJjBrVtqvO8BXXxn4+OOkC+zjY+Pnnx9gSMcmjOfPa2ja1MNhwmrPniYWLUrnmoopeC7WARZCiGdV/IQJqI8MedD+/jv6TZtysEV5U9euFpYsiUOjSeq3sVqVFMOvl5fKtGlx/PTTA3r1+v/27jysiav7A/h3MlkgAYwi4opWAQVEca8o7msVUX91t3Wpa1urvtUWrJVWW3Gp+mprsZW6guIuaOvSt8WKC2oXbd1al1K1tSgICglJSGZ+f0QCQ4IStiRwPs/DI7kZJje5Qc6cnHtvnuBao2dPPU6dykHv3uZZrpgYGXr3dsHvvzvGn0eOA779VljN2L+/dR8/v/pqHnbtUsPFRZgPO3RIgrAwBdLT7adcpzytWSOzGPwCwLVrLHr3dsF//yuFwYYVEZmZDF5+WWHWzyVLcvHee8Jgd9MmKe7cKflY6fXAl18KJ79NmaKzKvgFAF9fzjRhLl98vBTff2/f9eSO8RtOCCEOjGvRAnkjRgjaZFFRqBKzryrZ8OF5+OILYRBcmFTK4403tLh4MRtvvaUr9mPsOnV47NmjxpIluRCLhee6coVFz54uSEiobfcTei5eZAWZbFdXHp07Wx+x9emjxzff5KBuXWHG8/x5Mfr1U+D27aoVLqSmMvjsM2HwV3QDlrw8Bh984IzBgxVITa38i4DcXGDMGDn++EN4gTdjhhZvvqnD5Mk6NGxYMF46HYPly0tet5GYKFwxxMmJx6RJpav9nj1bC39/4ftuzhxnqFSlOl2lqFrvaEIIsVPa8HDwhdKQ7K1bkMTH27BHjmvEiDxER+eCYYQBy8iROly4kI2PP9aUqP5QJAJmzdLh+HEVmjQR/vFWqxl89FETvPmmMzjbfwperKNHhVm2Xr30Vmfw8rVqxeHbb3Pg5yd8LW7fZtGnjwLnzlWdkp3ISGdotQVBracnh19+ycbYseYB4NmzYnTt6orYWEmlXRAZDMDUqXKkpAjHd+hQHZYu1YBhAJkMCA8XZoF37pSU+NOL6GjhG2X0aF2p63alUmDdOuHv5J07IixdakeF1EVQAEwIIZWAa9oUeWPHCtqcVqwAiln2kTzbqFF52LdPjZ498zB6tA4nTmTjyy9z0bix9X/A27Y14OTJHIwYYT4WcXFSREWVfIesylZ0+Spryx+KatSIx9GjOejeXfjpxKNHIoSFVY0g+NQpFgkJwtft/fc1qF+fx+ef52LbNhVq1RJe9eTkMHjzTTnGj5dXeEkIzxtXpjh8WNjH4GA9NmzIFUxMHD06D76+BRcsHGdc+/p5LlxgceGCMLieObNs/xe1b2/A9OnCc0RHS/Hzz/b5nqEAmBBCKolm/nzwkoI/aqI7dyCNjbVhjxxbr156HDigxoYNuQgKKlua1s0N+PLLXKxfr4ZcLgyiV650wv79z15mrKSSk1lMneqMNWtkZc4s37/P4NKlguCCYXj07Vv2spoaNYA9e1QYM0YYzGg0DCZOlOPhQ8etCTYYgAULhLP6goL0GDu24MJhyBA9zp7NQb9+5hcTX38tQefOLmaZ9/K0Zo0MMTHCiy4/PwN27FCZlfSIxTCrBU5MlOCXX54ddBbN/vbpY91ujcVZuFAjKMvgOAazZjnb5TrLFAATQkgl4b28oJs4UdAm++QTQGPdzG1SMRjGuM1yUlIOatcWBgOvv+783KDiebZvl2DIEAX27DFuQb1qVdkyy0Unv7VrZ7B6GaziSKXA55/n4t13he/N+/dFmDJFbtOJYWURFyfBr78KxzEqyny5N09PHrt2qbFmTa7ZBdHDhyKMHq3AV1+VstbkGXbskGDxYmGU26ABh717VVAqLf/MkCF6BAUJL3wWLy7+vXX3LmOWAS9r9jefiwuwZo1w9YcrV1h8+qn9fYpCATAhhFQi7X/+A75QGkf0zz+Qbt5swx6Ropo35xAbq4ZYXBAEazQMxo2T499/S5f93L5dgrfechasP7xhg7RMFTBHjxYtfyjfSZUMA0REaDFnjjAI/uEHsV2XhRTnyRNgyRJhcDl8uK7YSYMMA0yapENycg7atzd/bRcudEJaWvllw7/7Toy33hJmp93ceOzZo0KDBsVf2DAMsGiRcBWGpCQJTp60fMEWEyMTLHnXvLkBvXqV33unb189Ro4UvrGXL5fh5k37CjntqzeEEFLF8fXqQffaa4I22erVsOvp0tXQiy8aEBHxl6Dtn39EGDdOjlwrlze1FPwCQEaGCEeOlO6jdI0GOHGibMufldTChVp07SoMkD75xAnHjtn3MldFrVrlhIcPhasefPjh8z99adaMw9GjKixYoBFsF56by+CTT8rnQuDqVRFefbVgt0PAuKLJjh0q+Ps/vzShZ0+92RgtXuxkNmkvJwfYskWYuZ45U1vuG1MuXaoR1FFrtQzeesu+JpRSAEwIIZVMO2cOeEXBzl2ihw8h3bjRhj0ilgwZkoHXXxdm1n76SYzZs51LvBpAbKzl4Dff9u2l+xj99GmxYPeu+vU5BAZWTHQhFgNffaU2WyJt+nRn/PWXY9QD//mnyKzuddYsLRo1KtlAisXAO++YbzCyZYu0zK8Bzxu3E1apCs7DMDy++CIXXbuWrNaEYYDISGHffvxRjG++EV6k7NwpxePHBY9TqxaHUaPK/8Kpdm3ebFOOM2fE2LatfGrpywMFwIQQUsl4Dw9oZ8wQtMnWrjV+RkvsyuLFGvTpIwwQdu+WYu3a5weusbESzJolDH4LZxAB48fe9+5ZH0AVnYTVv39euWfxCvP05PHVV2pB/7OyRJgwQe4QJewLFzoJdiqrX5/DnDnaZ/yEZZMm6eDlVXAhkJdn3dq7luzdKzFb7mzpUg2GDbMuMO3QwYCBA4U/89FHTqZ6bY4zlt0UNnmyrsJ2+hsxIs/sd2fRImfcv28fF00UABNCiA1oZ80C7+Zmui3KzIQsOtqGPSKWiMVATIwaPj7CTNyHHzo9s3zBUvArFvPYulWNVq0KzsXzDHbssC4LzPPmy5/161fxm6p06WIwyzJevChGRIT9rvUKAD/8wOLrr4WvV2SkBoU+hCkxqdR87d34+JKvvVuUSgVERgpfvwED8ko9Ke399zWCtXivXWOxZ4/xuR8/LsatWwV1wRIJj9deq7hlGBkGWL06FwpFQX+ePGEwf7597K1NATAhhNiCUgntG28ImmSffQbR1as26hApjlIJxMeroVQWZP54nsHUqXJcvWr+ZzQuznLwu2WLGoMH6/Hqq8KgIzZWalVt5PXrIty5I6xlLbpub0WZNUuHQYOEWb3Nm2WIj7efj7YL0+uBiAhhwNW+vR4jRpT+Y/9Ro/LQvLn1a+9asmaNDP/8UzCWEglvVmZhDX9/zuy5RUU5QacDoqOF9crDhuWhXr2K3dnDy4vHwoXC5+PkxENrffK93FEATAghNqKdORNczZqm20x2NhTDhkF0+7YNe0UsadaMw5YtwhKAnBwGo0crkJFREOjGxUnw5pvFB78A8PLLOjg5CXfMKm7GviVFJ59166aHXG71UyoVhgHWr1fjhReEGfG5c51x5Yr9hRTbt0tx9erzlz2zBssCCxZYv/ZuUampjNnyYK+/rkPTpmWr5V6wQCPY3vuvv0QID3fCDz8I3zdF69sryrRpOrRrp0fDhhx27VIhJiYXMjtYRMT+3q2EEFJduLlBGxEhaBKlpUERFgbm779t1ClSnB49DIiKEgY+d+4YZ+/rdMUHv5s3FwS/gDGjPGSIMEu3bVvJyyDMd3+rnOxvPqUS2LZNLQjic3MZTJggr7Ay9qwsIDzcCSNHyhEVJcNPP7HPzZpnZ7P46CNhpDVypA4dOpR9EWNLa+8WfaznWbTIfDvmefPKXlDdpAmPCROEnzJs2iTsW+fO+jJvHlNSLAts3qzG2bPZlf5efRYKgAkhxIZ0U6dCO22aoE109y4Uw4aBefjQRr0ixZk6VYeJE4WZs9OnxQgLUxQb/IaGmv/Rf+UVYYBy+LAEjx49f3JQZiZjth2xpR3LKlpgIIdPPhGuB3fzJotZs+QlXiGjpP75h8FLL7lgwwYZjh+XYPlyJ/Tu7QJfX1fMmOGMAwckyMoy/7mYmHrIyCgIc+Ry3qyGubQYBnj/feH74LvvJDh1qmRZ4JMnWSQmmtclu7qWS/cwf74Wzs7FD0RlZX/zeXnx5fbcygsFwIQQYksMA82yZdCNGSNoZv/4A4rhw2HxLzuxGYYBVqzQoEsXYVB79qy4xMEvAHTtahCUEeh0DHbvfn4d7f/+JwbHFTyOv7+hxEt5lbfx4/PMAvmEBInZcmNlceOGCP37u5iVMQBAeroI8fFSTJokR7NmbnjpJQX++18prl4V4eZNEXbtqiM4fvZs7TM3lLBWr156BAcXzQKbr71blF4PhIcL65LbtdNj9Ojyu5CpW5fH9OmWg9zGjTm89JL9ZGJthQJgQgixNZEIuZ9+irwhQwTN7G+/QTFqFG2SYWekUmMJQOPGlj9CFot5bNpUfPALGAPpV14xL4N4XvBUtP53wIDKz/4WtmJFLgIDhSUFixY5ISWlbNtGA8Avv7AYMECBu3efH6oYDAzOnBHjgw+cERzsii5dXGAwFPxcw4YcZs0q36yncQc2YUY5JUVstkV1UVu2mNclL19etrpkS+bM0cLNzfwNNX26FmzZh8fhUQBMCCH2QCyGeuNG5PXqJWw+dw7y8eNhF9OmiYm7O4+dO1VwcREGGPnB75Ahz8+wjRmjg0hU8PNXr7LPnEil1xszwIXZuqbS2dl4MVA40NLrGUyaJEdqaunXez1xgkVoqEJQwgAAvXrlISwsz2JgV1jh2loA+PBDTYVMFHzxRYPZDnyLFzsVW5+cmcng44+F9bijR+vQvn3Z65KLUiqNWe/CXF15jB9fcUufORIKgAkhxF7IZFBv3w59586CZklSEuSvvWaMgIjd8PfnsHGjGhKJMRizJvgFgHr1eLP1e5+1U9b58yyysgr+bNeqxVVI4GStF17gEB2tFrTdvy9Cx46uWLTIyeoqngMHJBgxQoGcHGEQO368Drt3q7F1qxq3bj3BoUM5mDVLixYtnv0avPiiHsOHV1ym/L33hFngy5dZHDxoeRyXLpUhM7NgDBWK8qtLtmTGDK1gDeu5c7UotPx4tUYBMCGE2BOFAqr4eBhatxY0Sw4fhvMbb8CqBWNJhRs4UI+kpBysWJGLlJScEge/+YrW0O7bJy224qXo6g99+ujt5qPsQYP0ZtlGnY7BunUytGnjiuhoKXQlSDxu3CjF5MnOyMsTBr9z52rw6ae5ED9NgEskQEiIAUuWaJCSkoNLl57gk09y0b9/nmDyl5sbjxUrcit0l7xWrTgMHy58ch9/LDO7Xr1yRYSvvhLWR8+bp63QtXgVCuDrr1VYvjwX27erMHcufZKUjwJgQgixNzVqQLVvHwy+voJm6a5dcHrnHZT7NHtSJi1bcpg2TQdvb+svTvr106NOnYKfy85mkJBgOXtoXv9rX58IvP++xqwcAAAyM0WIiHBGp04uSEgQW3z78rwxOzp/vnAlDQD4+ONcREZqnxnENm7MY8oUHXbtUuP27SfYs0eFRYv+RFJSDlq1qviLxgULtII1om/dYrFjR8E48rxx4lvhCYwvvGColNUY6tThMX26DqGh+gq9EHA0FAATQogd4mvXhurgQXBeXoJ2WUwMZEuW2KhXpLxJJMDYscLs4fbt5qsopKYyuH69IN3Lsjx69bLtBLiixGJgxw411q9Xo14986Dzzz9ZTJigwIABCly4UPBcDAZg3jwnrFgh3E1NLObxxRdqvPGGdTWrzs5A3756hIZmoFmzyvnExNubw9ixwvFYscIJmqfVDYcOiZGcLLyA+egjjV1sCFFdUQBMCCF2iq9fH6qEBHB16wranVavhmz5cmPkQBze+PHCwOnsWTFu3BD+eT5+XJgV7tzZAKWywrtmNZYFxo3Lw08/ZeO99zRmkwQB4Nw5Mfr2dcHEic64fl2EyZPl+OorYSTo7Mxj5041Ro2yryD/Wd55RwOptOD53rsnwubNUuTmAgsXCpc969kzj5YiszEKgAkhxI5xL7wA1YED4GrVErQ7RUXBJTgY4oMHqS7YwXl7c2bryRbNAhctf7BUamBP5HLjZgw//5yNyZOF5QH5Dh6U4sUXXc1KPpRKDgkJKvTt61gBYqNGPF57TZitXrVKhhUrZLhzpyDcYlkeUVEaKkewMQqACSHEznF+flDv2we+yFZK7O+/QzFxIly6dYP4m2+oNtiBFZ0Mt3OnBHlPY9ycHJh9fG7r5c9Kqk4dHqtXa3DmTE6J1iyuX5/DkSMqdOzomJ9u/Oc/WigUBb+H6ekirFkjLO2YMkWHFi3ootXWKAAmhBAHYGjTBqr4ePAuLmb3sZcvQzF2LBS9e0P8v/9RIOyAiq5t+/ChCEePGoPeEyfE0OmEk6d8fBwrgGrenEN8vBqHDuUgKMhy8O7jY8CxYznw83Os51aYhwePmTOLn9hWqxaHiIiKW/aMlBwFwIQQ4iAMXbog+9Qp6EaPBm9h2yjxzz9D8fLLUAwcCDY52QY9JKUllwMvvyzMAsfGGssgitb/9u/vuLP5Q0IM+P57Fb78Uo2GDQsC3Xbt9Dh6VGWzbZ3L05tvaqFUWg7iFy7U2mXtdnVEATAhhDgQvkkT5G7YgJyUFOiGD7d4jDglBS6hoVAMGQL23LlK7iEpraJbI3/7rRh//83g+HHHLH8ojkgEjByZhx9/zMaOHSps3arCsWMquLs7fvALGHdgmzPHPAvcsqUBEybQLmz2ggJgQghxQJyvL3I3bUL26dPIGzzY4jHikyfh0r8/5KNGgfn330ruIbFWUJABLVsW1L5yHIN333XGv/8W/Kl2ceHNJsw5Kicn4KWX9AgL05s2uKgqpk3TwdNTmAVetizXbjYuIRQAE0KIQ+MCAqCOjUX2iRPI69fP4jGSY8fg0qMH2PPnK7l3xBoMYz4Z7vBhYflDz556WjvWAcjlwBdfqOHqykMk4vHOOxp07eqYE/uqKgqACSGkCuCCgqDevRs5x49D37272f2if/+FYtAgSLZsqfS+kZIbOTIPMlnxpQD2vvwZKdCjhwG3bj1BauoTLFhAWxDbGwqACSGkCjF07AhVQgJyDh2CvmNHwX1MXh7kc+bAefZsQEt/kO1RzZo8QkOLD3IdbW3c6k4qBdzcbN0LYgkFwIQQUgUZQkKgOnIEmrlzze6Tbt0KxeDBYO7ft0HPyPMULYPI17atHp6eVWOiGCG2RgEwIYRUVSwLbWQkVFu2gJfLBXeJL1ww1gXTKhF2JyTEgMaNzZfRcvTVHwixJxQAE0JIFacfOhQ5334LwwsvCNpFaWlQDB4M6ebNtHmGHRGJgPHjzbPAVP9LSPmhAJgQQqoBLiAAOUlJyOvdW9DO5OXBee5cqgu2M2PH6sCyBRclDRtyaN3acXdII8TeUABMCCHVhVIJ9e7d0PznP2Z3Sbdtg2LQIDD//GODjpGiGjTg8fHHGkilPNzceHzySa7D7v5GiD2iAJgQQqoTloV20SKotm4Fr1AI7hL/+CNcevSAdMMGICvLRh0k+WbM0OHPP5/g99+fYMAAqv8lpDxRAEwIIdWQPizMcl3wgwdwDg+Hm58fnN98E+zPP1N9sA0pFICzs617QUjVQwEwIYRUU5y/v7EuuG9fs/uY3FxIY2Ph0qsXXHr0gGTrViAnxwa9JISQ8kcBMCGEVGdKJdTx8dDMnw9eLLZ4CHvpEuSzZ8PNzw9O8+ZBdOVKJXeSEELKFwXAhBBS3bEstO+9h+zffoPmvffANWxo8TAmOxuymBi4dukCxYABkMTHU1aYEOKQKAAmhBACAODr1YN2/nxkX7oEVXw88vr3B1/M0gPilBTIZ8yAm48P5K+8AsnevcCTJ5XcY0IIKR0KgAkhhAixLPQDBkC9axeyL16E5u23wdWpY/FQJjcXkkOHIJ8yxRgMjxljzAzTKhKEEDtGATAhhJBi8Y0bQ/v++8i+fBmqLVug79at2GMZrRaSI0cKMsMjR0ISFwcmM7MSe0wIIc9necYDIYQQUphUCv3QodAPHQrRjRuQbtsGycGDEN29a/FwJi8PkuPHITl+HLxYDH23buACA8E1bAiuUSPTF9zcKvmJEEIIBcCEEEKsxPn4QLNkCTSLF4O9eBGSgwchTkgAm5pq8XhGr4fk+++B7783u4+vUUMQEHONGoHz8gLXvDk4Hx+AZSv42RBCqiMKgAkhhJQOw8DQpg0MbdoAH3wA0a+/QpKYCMnBg2Bv3SrZKR4/Bvv4MdjLl83u4xUKGAIDYWjVCoagIBhatwbXvDlQzHJtAno9RHfuQPTHHxDduAH2xg2Ibt0CL5HA0LEj9N27w9C+PSCTWfusCSFVAAXAhBBCyo5hwLVuDW3r1tAuXAjR1auQJCRAkpgI9vr10p1SpYI4JQXilBRTG+/kBEPLlsaAuFUrGFq3BqPTGQPdmzeNge6NGxDdvg0mL8/ieSUnTgArVoB3doa+c2fou3WDoVs3GFq3powzIdUEBcDlaPTo0Th79iy6d++Obdu22bo7hBBiGwwDLiAA2oAAaBcsgOj338H+9BNEd++avpi7dyG6dw+MTmfdqTUaiH/8EeIffyx7N3NzIfn+e2N5BgDezQ36rl2h79YN+u7dKRgmpAqjALgcvf7665gwYQJ27txp664QQojd4Jo3N5YumN3BgXnwQBgU370L0e3bYC9dgigjo1L7yTx5Ask330DyzTcAgNY1a4IJDITB1xecjw84X18YfHzAN2gAFLM+crlSqyG6eRO8mxv4xo0r5zEJqSYoAC5H3bp1Q3Jysq27QQghjkEkAl+3Lgx168LQoYPwPp4H8/ffYC9eBHvpkvHr4kWIHjwo8em5OnXAeXuD8/GBwccHnI8PmIwMiH/4AeKTJyG6f/+ZPy/JzAROnoT45Elh1xQKcN7epsDY4OsLztsbfL164GvWBERWrjDK82Du3QN7+TLYK1cgunwZ7OXLEN26BYbnAQAGb2/khYZCHxpqrLmmYJiQMrFpALx69WocOnQIN2/ehFQqRfv27REZGQl/f/9yfZzTp0/j008/xaVLl3D//n2sX78e48aNMzsuJiYG69atQ1paGlq0aIGoqCgEBweXa18IIYSUAMOAb9gQ+oYNoR88uKD5/n1TMMxeugTRtWuAk5MgyOV8fGDw9gaUSounzhs7FuB5iG7dgvjkSYh/+AFscjJEjx6VrGsqlSkoL4pnWfDu7uBr1wZfuzY4Dw/jbQ+Pgu+VSoj+/LMg4L1yBaLnbBzC3rwJds0aYM0acA0bIm/wYOSFhsLw4oslL9XIyjI+5uXLYH/7DczDh+AaNwbn7w+Dnx8Mfn5AjRolOxchDs6mAfCpU6fw2muvoW3btuB5HkuXLsXQoUNx7tw51KxZ0+z4c+fOISgoCLIis3ZTU1PBMAwaN25s8XFUKhX8/f0xZswYzJgxw+Ix+/fvR3h4OFatWoUXX3wRMTExGDFiBFJSUtCoUSMAQOfOnS3+7J49e9CwYUNrnjohhJBS4OvVg75ePegHDCjbiRgGnLc3dN7e0E2eDHAcRFeuGLPDyckQnz4NJifH+tMaDGAePACsyFRbS3TvHmQbNkC2YQO42rWhHzTImB3u1g2QSo0Z5b/+Avvbb6Zgl/3tt2LXbC6Ma9gQBj8/cH5+MDwNjDlfX8DZucKeDyG2wGRlZfG27kS+nJwceHl5IS4uDgMHDhTcx/M8evTogbp16yI2NhYSiQQAcPfuXbz00ksYNmwYFi+hF9OCAAAS1UlEQVRe/NzHaNCgAVasWGGWAe7duzcCAgKwbt06U1vbtm0RFhaGyMjIEj+H5ORkbNy40W4mwd24cQM+Pj627gYpJRo/x0bj58D0etxNSsILWq1xZYn8VSZ+/x3MkyeV1g3OywvM/fvFrmhRGO/mBkOLFmCvXy/XPvIiEbimTcE3aADO3d2Yxc7Pcru7F7TVrg2+Vi3g6d9nW6PfP8dXkWNoVzXAOTk54DgOSgsfWzEMgz179mDQoEGYNGkStmzZgrS0NISGhqJDhw5WBalF6XQ6XLx4EbNmzRK09+rVC+fOnSv1eQkhhDgosRiaJk2g9/GBvnA7z4N5+BCiP/4oCIxv3IDozz8heviw1IEn7+ICQ0AADAEB4Fq2NC715ucHuLoCWVnGXfUOHYL4f/8Dk5tr8RzMkycQnz9fqsd/FobjwN68Cdy8WaLj+Ro1wNWsCdSoAT7/S6ks+L7ol7OzsYwj/0skAlgW/NN/82+DZY21z3o9kJcHGAzGC4OntxmDoeA+vR6ud+6AffQIvFwOuLiAl8vBKxSAXF7yOm2dDlCrweTkgFGrjd+rVIBMBq52bfAeHoBCUYZXl9iKXQXA4eHhCAwMRMeOHS3eX6dOHSQmJmLQoEGYOHEirl27hsDAQHz55Zdgy7BcTUZGBgwGAzw8PATtHh4eeGDFx1hhYWG4fPky1Go1/P39sWXLlmKfCyGEEAfEMODr1IGhTh0YunY1v1+rBZORYQyS09PBPHwIJj0dTHq6MUBOTweTmQnew8MY5AYEGLeIbty4+KBMqUTeyJHIGzkSUKkg/u47SA4fhuToUasCbp5lwTVvbnzcwEDwDRpAdOsWRFevgr12DaIbN4xBZBnlb25iaxbWHTHh5XJjYKxQgFcowMvlxiX51GowTwNeqNVg9PpnnKXQufLrvQvXfj8NkHk3t5JPWjQYwGg0xsfOzQU0GmN/cnONbRoNkJtrDMa1WmNgr1SCq1nTeJGR/2/hr5o1jRdSlT1xUqcD8/ix4Mvg6wveTkpG7SYAXrBgAVJSUnD06NFnBrP16tXDpk2bTOUQGzduhLgkuwKVAFPkzcHzvFnbsyQkJJRLPwghhDgomQx8/frg69cHVxHnVyigHzIE+iFDkKvTQXzypDEz/PXXEKWnmw7j3dyMge7TYNcQGAiuRQvAyan4c2u1xl3zrl2D6No1sFevgr16FaI7dyrimdgU8zTQRaHXrEznunPHrl8nnmWNwb5UCjg5Gf+VycDLZMbdEAt9z8tkBdn2fEVjocK39XqzQJd5/Nj4+hahXrcOea++WkHP0jp2EQBHRERg//79OHToEJo0afLMYzMyMvD666+jT58+uH79OubOnYv169dDZO2yM4W4u7uDZVmzbG96erpZVpgQQgixC1Ip9H36QN+nD7B6NdhffgGTmWnMsnl5WZ/xk8nAtWwJrmVLYXt2tjFTnJ5uzG6np4N59Kjgdv7X0+x2/tJtxH4wBgPw5AlsvXgeYwefDOSzeQD87rvvYv/+/Th8+DB8fX2feWxmZiaGDh2KevXqIS4uDvfv38egQYMwe/ZsrFu3zqpsbWFSqRRBQUFISkrC0KFDTe1JSUkYMmRIqc5JCCGEVBqWhaF9+4o5t6sruKCgkmW0DQZjEFwoE4jHj8FkZVnOEmZlGT/WNxgAjhP8y+R/n99uMAA8b5xkJxYDYjF4sdh4m2XB57c/va3WaCBnGDAqlbFuV6UqyPyWkClzWqh+mJfLwWg0xoD/4UOrdzOszpjnLPdXmWwaAM+bNw+7du1CbGwslEol0tLSAAAKhQIuLi6CY3mex8iRI1GrVi3ExcVBJpOhSZMmSExMxODBg/HRRx/h/ffft/g4OTk5uH37NgCA4zjcu3cPv/76K2rWrGla4uyNN97A9OnT0a5dO3Tq1AmbNm3Cv//+i0mTJlXgK0AIIYRUISxrqoO1tWJXEOA402Q2Rq0G8ie4SaUFge7ToBdS6bMz6TwPPHlizIYXqvkWPXxYUP+tUlnVb14uB5ydjf86ORknCcrl4Iu2yWTGyXmZmcYLCUv/Pn5s/NeKoL+88CKRYAIkatQA5+VV6f0ojk2XQbO02gNgzApHRESYtZ84cQIdO3aEXC4XtP/xxx8QiUTw9va2eL7k5GSEhoaatY8ZMwbR0dGm2zExMVi7di3S0tLg5+eHpUuXokuXLtY8JbtDy8A4Nho/x0bj59ho/BwbjV8hWq1x8pxOZ5xYp9MZJ2xqtcb78r/XaIz/Fp4MWbSkpehtlrW4ugdcXMo88a7KLoOWZWUqvEePHhbbn1c6ERISUqLHmjJlCqZMmWJVnwghhBBC7Fr+BLenN6lKGyj9zDFCCCGEEEIcEAXAhBBCCCGkWqEAmBBCCCGEVCsUABNCCCGEkGqFAmBCCCGEEFKt2HQZNEIIIYQQQiobZYAJIYQQQki1QgEwIYQQQgipVigAJoQQQggh1QoFwIQQQgghpFqhAJgQQgghhFQrFABXUTExMWjVqhU8PT3RvXt3nDlzxtZdIsU4ffo0Ro8eDT8/PyiVSsTFxQnu53keUVFRaNGiBerWrYtBgwbh2rVrNuotKWz16tXo2bMnGjVqhGbNmmHUqFG4evWq4BgaP/u1ceNGBAcHo1GjRmjUqBH69u2LY8eOme6nsXMsq1atglKpxPz5801tNIb2LSoqCkqlUvDl6+trur8ix48C4Cpo//79CA8Px9tvv42TJ0+iY8eOGDFiBO7evWvrrhELVCoV/P39sWzZMjg7O5vdv3btWqxfvx7Lly/H999/Dw8PDwwbNgzZ2dk26C0p7NSpU3jttddw7NgxJCYmQiwWY+jQocjMzDQdQ+Nnv+rXr48PP/wQP/zwA5KSktCtWzeMGzcOly9fBkBj50guXLiArVu3IiAgQNBOY2j/fHx88Pvvv5u+CifsKnL8aB3gKqh3794ICAjAunXrTG1t27ZFWFgYIiMjbdgz8jwNGjTAihUrMG7cOADGq98WLVpg6tSpmDdvHgAgNzcXPj4+WLJkCSZNmmTL7pIicnJy4OXlhbi4OAwcOJDGzwE1adIEkZGRmDhxIo2dg3j8+DG6d++OtWvXYsWKFfD398fKlSvp988BREVFITExEWfPnjW7r6LHjzLAVYxOp8PFixfRq1cvQXuvXr1w7tw5G/WKlNZff/2FtLQ0wXg6OzsjODiYxtMO5eTkgOM4KJVKADR+jsRgMGDfvn1QqVTo2LEjjZ0DmTNnDsLCwtC9e3dBO42hY0hNTYWfnx9atWqFyZMnIzU1FUDFj5+4zGcgdiUjIwMGgwEeHh6Cdg8PDzx48MBGvSKllZaWBgAWx/P+/fu26BJ5hvDwcAQGBqJjx44AaPwcwZUrV9CvXz9oNBooFArExsYiICDA9AeWxs6+bd26Fbdv38YXX3xhdh/9/tm/9u3b4/PPP4ePjw/S09OxcuVK9OvXDykpKRU+fhQAV1EMwwhu8zxv1kYcB42n/VuwYAFSUlJw9OhRsCwruI/Gz375+PggOTkZjx8/RmJiImbOnInDhw+b7qexs183btzA4sWLceTIEUil0mKPozG0X3379hXcbt++PYKCgrBjxw506NABQMWNH5VAVDHu7u5gWdYs25uenm52FUXsn6enJwDQeNq5iIgI7Nu3D4mJiWjSpImpncbP/kmlUjRt2hRt2rRBZGQkAgMD8fnnn9PYOYDz588jIyMDnTt3hru7O9zd3XH69GnExMTA3d0dtWrVAkBj6EhcXFzQokUL3L59u8J/BykArmKkUimCgoKQlJQkaE9KSkKnTp1s1CtSWo0bN4anp6dgPDUaDc6ePUvjaSfeffdd7N27F4mJiYLlewAaP0fEcRx0Oh2NnQMYNGgQzpw5g+TkZNNXmzZt8H//939ITk6Gt7c3jaGD0Wg0uHHjBjw9PSv8d5ANDw//oMxnIXbF1dUVUVFRqFu3LpycnLBy5UqcOXMGn332GWrUqGHr7pEicnJycP36daSlpWH79u3w9/eHm5sbdDodatSoAYPBgDVr1sDb2xsGgwHvvfce0tLS8N///hcymczW3a/W5s2bh/j4eGzZsgUNGzaESqWCSqUCYLwYZRiGxs+OffDBB5BKpeA4Dn///Teio6Oxe/dufPDBB2jWrBmNnZ1zcnKCh4eH4GvPnj3w8vLCuHHj6PfPASxcuND0O3jz5k3Mnz8ft2/fxpo1a6BUKit0/KgGuAoaPnw4Hj16hJUrVyItLQ1+fn7YvXs3vLy8bN01YsEvv/yC0NBQ0+2oqChERUVhzJgxiI6OxuzZs5Gbm4v58+cjKysL7dq1w/79++Hq6mrDXhPAuOEMAISFhQna3333XURERAAAjZ8dS0tLw7Rp0/DgwQO4ubkhICAAe/fuRe/evQHQ2FUFNIb27Z9//sGUKVOQkZGB2rVro3379vj2229N8UpFjh+tA0wIIYQQQqoVqgEmhBBCCCHVCgXAhBBCCCGkWqEAmBBCCCGEVCsUABNCCCGEkGqFAmBCCCGEEFKtUABMCCGEEEKqFQqACSGElCulUom5c+fauhuEEFIsCoAJIcTBxMXFQalUFvt19OhRW3eREELsGu0ERwghDio8PBwvvPCCWXurVq1s0BtCCHEcFAATQoiD6t27Nzp06GDrbhBCiMOhEghCCKmi8mtx9+/fj06dOsHT0xPBwcE4duyY2bF3797F1KlT0bRpU3h6eqJr167YuXOn2XE8z2Pjxo3o2rUr6tati6ZNm2Lo0KE4c+aM2bHffvstQkJC4OnpibZt22Lv3r2C+/V6PVauXIl27dqZztWvXz8kJCSU34tACCEWUAaYEEIc1JMnT5CRkWHW7u7ubvr+3LlzOHDgAKZPnw4XFxds3boV48aNQ0JCArp06QIAyMjIwIABA5CZmYlp06ahbt262L9/P2bOnImsrCzMnDnTdL7Zs2dj27Zt6NGjB8aOHQue53H+/HmcPXsWwcHBpuMuXLiAr7/+GpMmTcIrr7yCbdu2Ydq0aQgMDETz5s0BAMuWLcOqVavwyiuvoF27dlCpVPj111/x448/IiwsrKJeNkIIAZOVlcXbuhOEEEJKLi4uDm+88Uax99+7dw8uLi5QKpUAgGPHjqFTp04AgEePHqFt27bw9fXF8ePHAQALFy7EZ599hoSEBHTv3h0AoNPpMHDgQFy/fh1Xr15FjRo1kJycjNDQUEyYMAFr164VPCbP82AYBoAx8ywWi3H69GlTsPvgwQO0bNkS06dPx5IlSwAAISEhqF+/Pnbt2lWOrw4hhDwfZYAJIcRBLV++3BRgFubs7Gz6vk2bNqbgFwBq1aqFESNGYOPGjcjKyoJSqcSxY8fQqlUrU/ALAFKpFDNnzsSUKVNw6tQpDBo0CImJiQCMAXNR+cFvvpCQEEHf6tSpAx8fH6SmppraXF1dce3aNdy8eRPe3t7WvwCEEFJKFAATQoiDatu27XMnwTVr1qzYtrt370KpVOLOnTsIDQ01Oy4/gL1z5w4A4M8//4SHhwc8PDye27dGjRqZtSmVSmRmZppuR0REYPz48Wjfvj1atGiBXr164eWXX0bbtm2fe35CCCkLmgRHCCFVWNHMLGAsVyiJoscVLnN4HpZln3vOkJAQXLp0CdHR0WjVqhXi4+PRu3dvrF69ukSPQQghpUUBMCGEVGE3b940a7t9+zaAgiytl5cX/vjjD7Pjbty4YbofAJo2bYoHDx7g4cOH5dY/pVKJMWPG4Msvv8SVK1cQHByM5cuXw2AwlNtjEEJIURQAE0JIFfbLL7/g/PnzptuPHj3Cnj170KFDB9Mkuf79++PXX3/FyZMnTcfl5eVhw4YNkMvl6Nq1KwBgyJAhAIClS5eaPU5Js8qFPXr0SHDb2dkZzZs3h1arhVqttvp8hBBSUlQDTAghDuq7774zZXMLCwoKMtXv+vv7Y9SoUZg2bZppGbTs7GwsWrTIdHz+WsFjxozB9OnT4enpiQMHDuDChQtYunQpatSoAcBYsjB27Fhs3rwZqamp6NevHwDjkmcBAQF4++23rep/x44dERwcjLZt26JWrVq4fPkytm3bhv79+8PV1bW0LwshhDwXBcCEEOKgli1bZrF9yZIlpgC4U6dOCAkJwbJly5CamopmzZohNjYWISEhpuPd3d1x7NgxfPjhh9i8eTPUajW8vb0RHR2NMWPGCM792WefISAgANu3b0dkZCRcXFzQunVr05rC1pg5cyaOHDmCkydPQqPRoEGDBpgzZw7mzJlj9bkIIcQatA4wIYRUUUqlEpMmTcKaNWts3RVCCLErVANMCCGEEEKqFQqACSGEEEJItUIBMCGEEEIIqVZoEhwhhFRRWVlZtu4CIYTYJcoAE0IIIYSQaoUCYEIIIYQQUq1QAEwIIYQQQqoVCoAJIYQQQki1QgEwIYQQQgipVigAJoQQQggh1cr/A6zqJygc5G4qAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sbs_relu.plot_losses()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = figure5b(sbs_logistic, sbs_nn, sbs_relu)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show Me the Math Again!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "\\large\n",
    "\\begin{array}{rcccccccccccc}\n",
    "\\text{Hidden }\\#0 & & & & & & & &\n",
    "\\underset{(5 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "z_{00} \\\\\n",
    "z_{01} \\\\\n",
    "z_{02} \\\\\n",
    "z_{03} \\\\\n",
    "z_{04} \\\\\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "=\n",
    "&\n",
    "\\underset{(5 \\times 25)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{00} & -\\\\\n",
    "- & w^{T}_{01} & -\\\\\n",
    "- & w^{T}_{02} & -\\\\\n",
    "- & w^{T}_{03} & -\\\\\n",
    "- & w^{T}_{04} & -\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "&\n",
    "\\underset{(25 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "x_0 \\\\\n",
    "\\vdots \\\\\n",
    "x_{11} \\\\\n",
    "\\vdots \\\\\n",
    "x_{24}\n",
    "\\end{bmatrix}}\n",
    "\\\\\n",
    "\\text{Hidden }\\#1 & & & &\n",
    "\\underset{(3 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "z_{10} \\\\\n",
    "z_{11} \\\\\n",
    "z_{12} \\\\\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "=\n",
    "&\n",
    "\\underset{(3 \\times 5)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{10} & -\\\\\n",
    "- & w^{T}_{11} & -\\\\\n",
    "- & w^{T}_{12} & -\\\\\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "&\n",
    "\\underbrace{\n",
    "f_0\n",
    "\\underset{(5 \\times 1)}{\n",
    "\\left(\n",
    "\\begin{bmatrix}\n",
    "z_{00} \\\\\n",
    "z_{01} \\\\\n",
    "z_{02} \\\\\n",
    "z_{03} \\\\\n",
    "z_{04} \\\\\n",
    "\\end{bmatrix}\n",
    "\\right)}}_{\\text{Activation #0}}\n",
    "\\\\\n",
    "\\text{Output} &\n",
    "\\underset{(1 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "z_{2}\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "=\n",
    "&\n",
    "\\underset{(1 \\times 3)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{20} & -\\\\\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "\\underbrace{\n",
    "f_1\n",
    "\\underset{(3 \\times 1)}{\n",
    "\\left(\n",
    "\\begin{bmatrix}\n",
    "z_{10} \\\\\n",
    "z_{11} \\\\\n",
    "z_{12} \\\\\n",
    "\\end{bmatrix}\n",
    "\\right)}}_{\\text{Activation #1}}\n",
    "\\\\\n",
    "\\hline\n",
    "\\text{substituting z's...} &\n",
    "\\underset{(1 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "z_{2}\n",
    "\\end{bmatrix}}\n",
    "&\n",
    "=\n",
    "&\n",
    "\\underbrace{\n",
    "\\underset{(1 \\times 3)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{20} & -\\\\\n",
    "\\end{bmatrix}}}_{\\text{Output Layer}}\n",
    "&\n",
    "f_1\n",
    "& &\n",
    "\\left(\n",
    "\\underbrace{\n",
    "\\underset{(3 \\times 5)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{10} & -\\\\\n",
    "- & w^{T}_{11} & -\\\\\n",
    "- & w^{T}_{12} & -\\\\\n",
    "\\end{bmatrix}}}_{\\text{Hidden Layer #1}}\n",
    "\\right.\n",
    "&\n",
    "&\n",
    "f_0\n",
    "& &\n",
    "\\left(\n",
    "\\underbrace{\n",
    "\\underset{(5 \\times 25)}{\n",
    "\\begin{bmatrix}\n",
    "- & w^{T}_{00} & -\\\\\n",
    "- & w^{T}_{01} & -\\\\\n",
    "- & w^{T}_{02} & -\\\\\n",
    "- & w^{T}_{03} & -\\\\\n",
    "- & w^{T}_{04} & -\n",
    "\\end{bmatrix}}}_{\\text{Hidden Layer #0}}\n",
    "\\right.\n",
    "&\n",
    "&\n",
    "\\left.\n",
    "\\left.\n",
    "\\underbrace{\n",
    "\\underset{(25 \\times 1)}{\n",
    "\\begin{bmatrix}\n",
    "x_0 \\\\\n",
    "\\vdots \\\\\n",
    "x_{11} \\\\\n",
    "\\vdots \\\\\n",
    "x_{24}\n",
    "\\end{bmatrix}}}_{\\text{Inputs}}\n",
    "\\right)\n",
    "\\right)\n",
    "\\end{array}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Putting It All Together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TransformedTensorDataset(Dataset):\n",
    "    def __init__(self, x, y, transform=None):\n",
    "        self.x = x\n",
    "        self.y = y\n",
    "        self.transform = transform\n",
    "        \n",
    "    def __getitem__(self, index):\n",
    "        x = self.x[index]\n",
    "        \n",
    "        if self.transform:\n",
    "            x = self.transform(x)\n",
    "        \n",
    "        return x, self.y[index]\n",
    "        \n",
    "    def __len__(self):\n",
    "        return len(self.x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "def index_splitter(n, splits, seed=13):\n",
    "    idx = torch.arange(n)\n",
    "    # Makes the split argument a tensor\n",
    "    splits_tensor = torch.as_tensor(splits)\n",
    "    # Finds the correct multiplier, so we don't have\n",
    "    # to worry about summing up to N (or one)\n",
    "    multiplier = n / splits_tensor.sum()    \n",
    "    splits_tensor = (multiplier * splits_tensor).long()\n",
    "    # If there is a difference, throws at the first split\n",
    "    # so random_split does not complain\n",
    "    diff = n - splits_tensor.sum()\n",
    "    splits_tensor[0] += diff\n",
    "    # Uses PyTorch random_split to split the indices\n",
    "    torch.manual_seed(seed)\n",
    "    return random_split(idx, splits_tensor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_balanced_sampler(y):\n",
    "    # Computes weights for compensating imbalanced classes\n",
    "    classes, counts = y.unique(return_counts=True)\n",
    "    weights = 1.0 / counts.float()\n",
    "    sample_weights = weights[y.squeeze().long()]\n",
    "    # Builds sampler with compute weights\n",
    "    generator = torch.Generator()\n",
    "    sampler = WeightedRandomSampler(\n",
    "        weights=sample_weights,\n",
    "        num_samples=len(sample_weights),\n",
    "        generator=generator,\n",
    "        replacement=True\n",
    "    )\n",
    "    return sampler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Builds tensors from numpy arrays BEFORE split\n",
    "# Modifies the scale of pixel values from [0, 255] to [0, 1]\n",
    "x_tensor = torch.as_tensor(images / 255).float()\n",
    "y_tensor = torch.as_tensor(labels.reshape(-1, 1)).float()\n",
    "\n",
    "# Uses index_splitter to generate indices for training and\n",
    "# validation sets\n",
    "train_idx, val_idx = index_splitter(len(x_tensor), [80, 20])\n",
    "# Uses indices to perform the split\n",
    "x_train_tensor = x_tensor[train_idx]\n",
    "y_train_tensor = y_tensor[train_idx]\n",
    "x_val_tensor = x_tensor[val_idx]\n",
    "y_val_tensor = y_tensor[val_idx]\n",
    "\n",
    "# Builds different composers because of data augmentation on training set\n",
    "train_composer = Compose([RandomHorizontalFlip(p=.5),\n",
    "                          Normalize(mean=(.5,), std=(.5,))])\n",
    "val_composer = Compose([Normalize(mean=(.5,), std=(.5,))])\n",
    "# Uses custom dataset to apply composed transforms to each set\n",
    "train_dataset = TransformedTensorDataset(x_train_tensor, y_train_tensor, transform=train_composer)\n",
    "val_dataset = TransformedTensorDataset(x_val_tensor, y_val_tensor, transform=val_composer)\n",
    "\n",
    "# Builds a weighted random sampler to handle imbalanced classes\n",
    "sampler = make_balanced_sampler(y_train_tensor)\n",
    "\n",
    "# Uses sampler in the training set to get a balanced data loader\n",
    "train_loader = DataLoader(dataset=train_dataset, batch_size=16, sampler=sampler)\n",
    "val_loader = DataLoader(dataset=val_dataset, batch_size=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sets learning rate - this is \"eta\" ~ the \"n\" like Greek letter\n",
    "lr = 0.1\n",
    "\n",
    "torch.manual_seed(11)\n",
    "# Now we can create a model\n",
    "model_relu = nn.Sequential()\n",
    "model_relu.add_module('flatten', nn.Flatten())\n",
    "model_relu.add_module('hidden0', nn.Linear(25, 5, bias=False))\n",
    "model_relu.add_module('activation0', nn.ReLU())\n",
    "model_relu.add_module('hidden1', nn.Linear(5, 3, bias=False))\n",
    "model_relu.add_module('activation1', nn.ReLU())\n",
    "model_relu.add_module('output', nn.Linear(3, 1, bias=False))\n",
    "model_relu.add_module('sigmoid', nn.Sigmoid())\n",
    "\n",
    "# Defines a SGD optimizer to update the parameters\n",
    "# (now retrieved directly from the model)\n",
    "optimizer_relu = optim.SGD(model_relu.parameters(), lr=lr)\n",
    "\n",
    "# Defines a binary cross entropy loss function\n",
    "binary_loss_fn = nn.BCELoss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_epochs = 50\n",
    "\n",
    "sbs_relu = StepByStep(model_relu, binary_loss_fn, optimizer_relu)\n",
    "sbs_relu.set_loaders(train_loader, val_loader)\n",
    "sbs_relu.train(n_epochs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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